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  • MPI Ethno. Forsch.  (187)
  • KOBV
  • Birmingham, UK : Packt Publishing  (157)
  • Sebastopol, CA : O'Reilly  (29)
  • Leiden : Brill
  • Open source software  (101)
  • Data mining  (87)
Datasource
  • MPI Ethno. Forsch.  (187)
  • KOBV
Material
Language
Years
Author, Corporation
Publisher
Keywords
Subjects(RVK)
  • 1
    Online Resource
    Online Resource
    Principles of data science : a beginner's guide to essential math and coding skills for data fluency and machine learning (2024)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781837636303
    Language: English
    Pages: 1 online resource (326 pages) , illustrations
    Edition: Third edition.
    DDC: 005.75/65
    Keywords: Data mining ; Quantitative research
    Abstract: Transform your data into insights with must-know techniques and mathematical concepts to unravel the secrets hidden within your data Key Features Learn practical data science combined with data theory to gain maximum insights from data Discover methods for deploying actionable machine learning pipelines while mitigating biases in data and models Explore actionable case studies to put your new skills to use immediately Purchase of the print or Kindle book includes a free PDF eBook Book Description Principles of Data Science bridges mathematics, programming, and business analysis, empowering you to confidently pose and address complex data questions and construct effective machine learning pipelines. This book will equip you with the tools to transform abstract concepts and raw statistics into actionable insights. Starting with cleaning and preparation, you'll explore effective data mining strategies and techniques before moving on to building a holistic picture of how every piece of the data science puzzle fits together. Throughout the book, you'll discover statistical models with which you can control and navigate even the densest or the sparsest of datasets and learn how to create powerful visualizations that communicate the stories hidden in your data. With a focus on application, this edition covers advanced transfer learning and pre-trained models for NLP and vision tasks. You'll get to grips with advanced techniques for mitigating algorithmic bias in data as well as models and addressing model and data drift. Finally, you'll explore medium-level data governance, including data provenance, privacy, and deletion request handling. By the end of this data science book, you'll have learned the fundamentals of computational mathematics and statistics, all while navigating the intricacies of modern ML and large pre-trained models like GPT and BERT. What you will learn Master the fundamentals steps of data science through practical examples Bridge the gap between math and programming using advanced statistics and ML Harness probability, calculus, and models for effective data control Explore transformative modern ML with large language models Evaluate ML success with impactful metrics and MLOps Create compelling visuals that convey actionable insights Quantify and mitigate biases in data and ML models Who this book is for If you are an aspiring novice data scientist eager to expand your knowledge, this book is for you. Whether you have basic math skills and want to apply them in the field of data science, or you excel in programming but lack the necessary mathematical foundations, you'll find this book useful. Familiarity with Python programming will further enhance your learning experience.
    Note: Includes index
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    SQL for data analytics : harness the power of SQL to extract insights from data (2022)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781801812870
    Language: English
    Pages: 1 online resource (540 pages) , illustrations
    Edition: Third edition.
    DDC: 005.13/3
    Keywords: SQL (Computer program language) ; Data mining ; Electronic books
    Abstract: Every day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace. This book helps you analyze this data and identify key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. SQL for Data Analytics, Third Edition is a great way to get started with data analysis, showing how to effectively sort and process information from raw data, even without any prior experience. You will begin by learning how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you will learn how to write SQL queries to aggregate, calculate, and combine SQL data from sources outside of your current dataset. You will also discover how to work with advanced data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you will be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation. By the end of this book, you will be proficient in the efficient application of SQL techniques in everyday business scenarios and looking at data with the critical eye of analytics professional.
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Applied unsupervised learning with R (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789951462 , 1789951461
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: R (Computer program language) ; Machine learning ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key Features Build state-of-the-art algorithms that can solve your business' problems Learn how to find hidden patterns in your data Revise key concepts with hands-on exercises using real-world datasets Book Description Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection. What you will learn Implement clustering methods such as k-means, agglomerative, and divisive Write code in R to analyze market segmentation and consumer behavior Estimate distribution and probabilities of different outcomes Implement dimension reduction using principal component analysis Apply anomaly detection methods to identify fraud Design algorithms with R and learn how to edit or improve code Who this book is for Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including ex...
    Note: Includes bibliographical references. - Description based on online resource; title from copyright page (Safari, viewed May 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789956399/?ar
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    Online Resource
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  • 4
    Online Resource
    Online Resource
    Hands-on business intelligence with Qlik Sense : implement self-service data analytics with insights and guidance from Qlik Sense experts (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789800593 , 1789800595
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Management information systems ; Business intelligence ; Computer programs ; Information visualization ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Create dynamic dashboards to bring interactive data visualization to your enterprise using Qlik Sense Key Features Implement various Qlik Sense features to create interactive dashboards Analyze data easily and make business decisions faster using Qlik Sense Perform self-service data analytics and geospatial analytics using an example-based approach Book Description Qlik Sense allows you to explore simple-to-complex data to reveal hidden insights and data relationships to make business-driven decisions. Hands-On Business Intelligence with Qlik Sense begins by helping you get to grips with underlying Qlik concepts and gives you an overview of all Qlik Sense's features. You will learn advanced modeling techniques and learn how to analyze the data loaded using a variety of visualization objects. You'll also be trained on how to share apps through Qlik Sense Enterprise and Qlik Sense Cloud and how to perform aggregation with AGGR. As you progress through the chapters, you'll explore the stories feature to create data-driven presentations and update an existing story. This book will guide you through the GeoAnalytics feature with the geo-mapping object and GeoAnalytics connector. Furthermore, you'll learn about the self-service analytics features and perform data forecasting using advanced analytics. Lastly, you'll deploy Qlik Sense apps for mobile and tablet. By the end of this book, you will be well-equipped to run successful business intelligence applications using Qlik Sense's functionality, data modeling techniques, and visualization best practices. What you will learn Discover how to load, reshape, and model data for analysis Apply data visualization practices to create stunning dashboards Make use of Python and R for advanced analytics Perform geo-analysis to create visualizations using native objects Learn how to work with AGGR and data stories Who this book is for If you're a data analyst, BI developer, or interested in business intelligence and want to gain practical experience of working on Qlik Sense, this book is for you. You'll also find it useful if you want to explore Qlik Sense's next-generation applications for self-service business intelligence. No prior experience of working with Qlik Sense is required.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789800944/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    Data wrangling with Python (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789804249 , 1789804248
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Data mining ; Electronic data processing ; Information visualization ; Electronic books ; local ; Electronic books
    Abstract: Simplify your ETL processes with these hands-on data hygiene tips, tricks, and best practices. Key Features Focus on the basics of data wrangling Study various ways to extract the most out of your data in less time Boost your learning curve with bonus topics like random data generation and data integrity checks Book Description For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain. The book starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The book will further help you grasp concepts through real-world examples and datasets. By the end of this book, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently. What you will learn Use and manipulate complex and simple data structures Harness the full potential of DataFrames and numpy.array at run time Perform web scraping with BeautifulSoup4 and html5lib Execute advanced string search and manipulation with RegEX Handle outliers and perform data imputation with Pandas Use descriptive statistics and plotting techniques Practice data wrangling and modeling using data generation techniques Who this book is for Data Wrangling with Python is designed for developers, data analysts, and business analysts who are keen to pursue a career as a full-fledged data scientist or analytics expert. Although, this book is for beginners, prior working knowledge of Python is necessary to easily grasp the concepts covered here. It will also help to have rudimentary knowledge of relational database and SQL.
    Note: Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: lizenzpflichtig
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    Online Resource
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  • 6
    Online Resource
    Online Resource
    Mastering MongoDB 4.x : expert techniques to run high-volume and fault-tolerant database solutions using MongoDB 4.x (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789611380 , 1789611385
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: MongoDB ; Open source software ; Object-oriented databases ; Database management ; Software ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of MongoDB 4.x to build and administer fault-tolerant database applications Key Features Master the new features and capabilities of MongoDB 4.x Implement advanced data modeling, querying, and administration techniques in MongoDB Includes rich case-studies and best practices followed by expert MongoDB developers Book Description MongoDB is the best platform for working with non-relational data and is considered to be the smartest tool for organizing data in line with business needs. The recently released MongoDB 4.x supports ACID transactions and makes the technology an asset for enterprises across the IT and fintech sectors. This book provides expertise in advanced and niche areas of managing databases (such as modeling and querying databases) along with various administration techniques in MongoDB, thereby helping you become a successful MongoDB expert. The book helps you understand how the newly added capabilities function with the help of some interesting examples and large datasets. You will dive deeper into niche areas such as high-performance configurations, optimizing SQL statements, configuring large-scale sharded clusters, and many more. You will also master best practices in overcoming database failover, and master recovery and backup procedures for database security. By the end of the book, you will have gained a practical understanding of administering database applications both on premises and on the cloud; you will also be able to scale database applications across all servers. What you will learn Perform advanced querying techniques such as indexing and expressions Configure, monitor, and maintain a highly scalable MongoDB environment Master replication and data sharding to optimize read/write performance Administer MongoDB-based applications on premises or on the cloud Integrate MongoDB with big data sources to process huge amounts of data Deploy MongoDB on Kubernetes containers Use MongoDB in IoT, mobile, and serverless environments Who this book is for This book is ideal for MongoDB developers and database administrators who wish to become successful MongoDB experts and build scalable and fault-tolerant applications using MongoDB. It will also be useful for database professionals who wish to become certified MongoDB professionals. Some understanding of MongoDB and basic database concepts is required to get the most out of this book.
    Note: Previous edition published: 2017. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789617870/?ar
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  • 7
    Online Resource
    Online Resource
    Drupal 8 module development : build modules and themes using the latest version of Drupal 8 (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789807868 , 1789807867
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Drupal (Computer file) ; Web sites ; Authoring programs ; Web site development ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Learn to create and customize impressive Drupal 8 modules to extend your website's functionalities Key Features Explore a plethora of Drupal 8 APIs and get the best out of them using the power of PHP coding Learn to implement efficient data management and data security by creating dedicated modules for it. Stay up to date with the changes introduced in the new Drupal 8 releases Book Description Drupal 8 comes with a release cycle that allows for new functionality to be added at a much faster pace. However, this also means code deprecations and changing architecture that you need to stay on top of. This book updates the first edition and includes the new functionality introduced in versions up to, and including 8.7. The book will first introduce you to the Drupal 8 architecture and its subsystems before diving into creating your first module with basic functionality. You will work with the Drupal logging and mailing systems, learn how to output data using the theme layer and work with menus and links programmatically. Then, you will learn how to work with different kinds of data storages, create custom entities, field types and leverage the Database API for lower level database queries. You will further see how to introduce JavaScript into your module, work with the various file systems and ensure the code you write works on multilingual sites. Finally, you will learn how to programmatically work with Views, write automated tests for your functionality and also write secure code in general. By the end, you will have learned how to develop your own custom module that can provide complex business solutions. And who knows, maybe you'll even contribute it back to the Drupal community. What you will learn Develop Drupal 8 modules that do all the things you want Master numerous Drupal 8 sub-systems and APIs in the process Model, store, manipulate and process data to serve your purposes Display data and content in a clean and secure way using the Drupal 8 theme system Test your business logic to prevent regressions Stay ahead of the curve and write code following the current best practices Who this book is for The primary target of this book is Drupal developers who want to learn how to write modules and develop in Drupal 8. It is also intended for Drupal site builders and PHP developers who have basic Object Oriented Programming skills. A little bit of Symfony experience is helpful but not mandatory.
    Note: Previous edition published: 2017. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789612363/?ar
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  • 8
    Online Resource
    Online Resource
    Learn Chart.js : create interactive visualizations for the Web with Chart.js 2 (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789342154 , 1789342155
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Charts, diagrams, etc ; Computer programs ; JavaScript (Computer program language) ; Information visualization ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Design interactive graphics and visuals for your data-driven applications using the popular open-source Chart.js data visualization library. Key Features Harness the power of JavaScript, HTML, and CSS to create interactive visualizations Display quantitative information efficiently in the form of attractive charts by using Chart.js A practical guide for creating data-driven applications using open-source JavaScript library Book Description Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library. If you want to quickly create responsive Web-based data visualizations for the Web, Chart.js is a great choice. This book guides the reader through dozens of practical examples, complete with code you can run and modify as you wish. It is a practical hands-on introduction to Chart.js. If you have basic knowledge of HTML, CSS and JavaScript you can learn to create beautiful interactive Web Canvas-based visualizations for your data using Chart.js. This book will help you set up Chart.js in a Web page and show how to create each one of the eight Chart.js chart types. You will also learn how to configure most properties that override Chart's default styles and behaviors. Practical applications of Chart.js are exemplified using real data files obtained from public data portals. You will learn how to load, parse, filter and select the data you wish to display from those files. You will also learn how to create visualizations that reveal patterns in the data. This book is based on Chart.js version 2.7.3 and ES2015 JavaScript. By the end of the book, you will be able to create beautiful, efficient and interactive data visualizations for the Web using Chart.js. What you will learn Learn how to create interactive and responsive data visualizations using Chart.js Learn how to create Canvas-based graphics without Canvas programming Create composite charts and configure animated data updates and transitions Efficiently display quantitative information using bar and line charts, scatterplots, and pie charts Learn how to load, parse, and filter external files in JSON and CSV formats Understand the benefits of using a data visualization framework Who this book is for The ideal target audience of this book includes web developers and designers, data journalists, data scientists and artists who wish to create interactive data visualizations...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789342482/?ar
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  • 9
    Online Resource
    Online Resource
    Machine learning with the Elastic Stack : expert techniques to integrate machine learning with distributed search and analytics (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788471770 , 1788471776
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Information visualization ; Electronic data processing ; Distributed processing ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Leverage Elastic Stack's machine learning features to gain valuable insight from your data Key Features Combine machine learning with the analytic capabilities of Elastic Stack Analyze large volumes of search data and gain actionable insight from them Use external analytical tools with your Elastic Stack to improve its performance Book Description Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure. By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly. What you will learn Install the Elastic Stack to use machine learning features Understand how Elastic machine learning is used to detect a variety of anomaly types Apply effective anomaly detection to IT operations and security analytics Leverage the output of Elastic machine learning in custom views, dashboards, and proactive alerting Combine your created jobs to correlate anomalies of different layers of infrastructure Learn various tips and tricks to get the most out of Elastic machine learning Who this book is for If you are a data professional eager to gain insight on Elasticsearch data without having to rely on a machine learning specialist or custom development, Machine Learning with the Elastic Stack is for you. Those looking to integrate machine learning within their search and analytics applications will also find this book very useful. Prior experience with the Elastic Stack is needed to get the most out of this book.
    Note: Description based on online resource; title from title page (Safari, viewed March 22, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788477543/?ar
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  • 10
    Online Resource
    Online Resource
    Go web scraping quick start guide : implement the power of Go to scrape and crawl data from the web (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789612943 , 1789612942
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Go (Computer program language) ; Data mining ; Internet searching ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Learn how some Go-specific language features help to simplify building web scrapers along with common pitfalls and best practices regarding web scraping. Key Features Use Go libraries like Goquery and Colly to scrape the web Common pitfalls and best practices to effectively scrape and crawl Learn how to scrape using the Go concurrency model Book Description Web scraping is the process of extracting information from the web using various tools that perform scraping and crawling. Go is emerging as the language of choice for scraping using a variety of libraries. This book will quickly explain to you, how to scrape data data from various websites using Go libraries such as Colly and Goquery. The book starts with an introduction to the use cases of building a web scraper and the main features of the Go programming language, along with setting up a Go environment. It then moves on to HTTP requests and responses and talks about how Go handles them. You will also learn about a number of basic web scraping etiquettes. You will be taught how to navigate through a website, using a breadth-first and then a depth-first search, as well as find and follow links. You will get to know about the ways to track history in order to avoid loops and to protect your web scraper using proxies. Finally the book will cover the Go concurrency model, and how to run scrapers in parallel, along with large-scale distributed web scraping. What you will learn Implement Cache-Control to avoid unnecessary network calls Coordinate concurrent scrapers Design a custom, larger-scale scraping system Scrape basic HTML pages with Colly and JavaScript pages with chromedp Discover how to search using the "strings" and "regexp" packages Set up a Go development environment Retrieve information from an HTML document Protect your web scraper from being blocked by using proxies Control web browsers to scrape JavaScript sites Who this book is for Data scientists, and web developers with a basic knowledge of Golang wanting to collect web data and analyze them for effective reporting and visualization.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789615708/?ar
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  • 11
    Online Resource
    Online Resource
    Kibana 7 quick start guide : visualize your Elasticsearch data with ease (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789808490 , 1789808499
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Information visualization ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: A quick start guide to visualize your Elasticsearch data Key Features Your hands-on guide to visualizing the Elasticsearch data as well as navigating the Elastic stack Work with different Kibana plugins and create effective machine learning jobs using Kibana Build effective dashboards and reports without any hassle Book Description The Elastic Stack is growing rapidly and, day by day, additional tools are being added to make it more effective. This book endeavors to explain all the important aspects of Kibana, which is essential for utilizing its full potential. This book covers the core concepts of Kibana, with chapters set out in a coherent manner so that readers can advance their learning in a step-by-step manner. The focus is on a practical approach, thereby enabling the reader to apply those examples in real time for a better understanding of the concepts and to provide them with the correct skills in relation to the tool. With its succinct explanations, it is quite easy for a reader to use this book as a reference guide for learning basic to advanced implementations of Kibana. The practical examples, such as the creation of Kibana dashboards from CSV data, application RDBMS data, system metrics data, log file data, APM agents, and search results, can provide readers with a number of different drop-off points from where they can fetch any type of data into Kibana for the purpose of analysis or dashboarding. What you will learn Explore how Logstash is configured to fetch CSV data Understand how to create index patterns in Kibana Become familiar with how to apply filters on data Discover how to create ML jobs Explore how to analyze APM data from APM agents Get to grips with how to save, share, inspect, and edit visualizations Understand how to find an anomaly in data Who this book is for Kibana 7 Quick Start Guide is for developers new to Kibana who want to learn the fundamentals of using the tool for visualization, as well as existing Elastic developers.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 26, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789804034/?ar
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  • 12
    Online Resource
    Online Resource
    Ancient manuscripts in digital culture : visualisation, data mining, communication (2019)
    Leiden : Brill
    Details
    ISBN: 9789004399297 , 9004399291
    Language: English
    Pages: 1 Online-Ressource
    Series Statement: Digital biblical studies volume 3
    Keywords: Bible Criticism, interpretation, etc ; Data processing ; Manuscripts Digitization ; Jewish religious literature History and criticism ; Data processing ; Communication in learning and scholarship Technological innovations ; Data mining ; Digital humanities ; Christian literature, Early History and criticism ; Data processing ; Bible ; Communication in learning and scholarship ; Technological innovations ; Data mining ; Digital humanities ; Electronic data processing ; RELIGION / Biblical Studies / Exegesis & Hermeneutics ; Criticism, interpretation, etc
    Abstract: Introduction: the Dissemination of the Digital Humanities within Research on Biblical, Early Jewish and Christian Studies / Claire Clivaz, David Hamidovic, and Sarah Bowen Savant -- Part 1. Visualising the Manuscripts -- Digitization and Manuscripts as Visual Objects: Reflections from a Media -- Studies Perspective / Liv Ingeborg Lied -- The Power of Visual Culture and the Fragility of the Text / Peter M. Phillips -- "What no eye has seen": Using a Digital Microscope to Edit Papyrus -- Fragments of Early Christian Apocryphal Writings / Brent Landau, Adeline Harrington, and James C. Henriques -- Manuscripts, Monks, and Mufattishin: Digital Access and Concerns of Cultural Heritage in the Yale Monastic Archaeology Project / Stephen J. Davis -- Part 2. Data Mining and Visualisation -- Qualitative Analysis of Semantic Language Models / Thibault Clerice and Matthew Munson -- Using Natural Language Processing to Search for Textual References / Brett Graham -- Electronic Transcriptions of New Testament Manuscripts and Their Accuracy, Documentation and Publication / H.A.G. Houghton -- Visualizing Data in the Quantitative Comparison of Ancient Texts: a Study of Paul, Epictetus, and Philodemus / Paul Robertson -- Part 3. Communication -- Teaching Epigraphy in the Digital Age / Heather Dana, Davis Parker, and Christopher A. Rollston -- Harvard X's Early Christianity: the Letters of Paul: a Retrospective on Online Teaching and Learning / Jennifer Aileen Quigley and Laura Salah Nasrallah -- Learning from Jesus' Wife: What Does Forgery Have to Do with the Digital Humanities? / James F. McGrath -- Synagogue Modeling Project Report: a Multi-faceted Approach to 3D, Academic Modeling / Bradley C. Erickson.
    Note: Includes bibliographical references and index
    URL: kostenfrei
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  • 13
    Online Resource
    Online Resource
    R web scraping quick start guide : techniques and tools to crawl and scrape data from websites (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788992633 , 1788992636
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: R (Computer program language) ; Data mining ; Information retrieval ; Electronic books ; Electronic books ; local
    Abstract: Web Scraping techniques are getting more popular, since data is as valuable as oil in 21st century. Through this book get some key knowledge about using XPath, regEX; web scraping libraries for R like rvest and RSelenium technologies. Key Features Techniques, tools and frameworks for web scraping with R Scrape data effortlessly from a variety of websites Learn how to selectively choose the data to scrape, and build your dataset Book Description Web scraping is a technique to extract data from websites. It simulates the behavior of a website user to turn the website itself into a web service to retrieve or introduce new data. This book gives you all you need to get started with scraping web pages using R programming. You will learn about the rules of RegEx and Xpath, key components for scraping website data. We will show you web scraping techniques, methodologies, and frameworks. With this book's guidance, you will become comfortable with the tools to write and test RegEx and XPath rules. We will focus on examples of dynamic websites for scraping data and how to implement the techniques learned. You will learn how to collect URLs and then create XPath rules for your first web scraping script using rvest library. From the data you collect, you will be able to calculate the statistics and create R plots to visualize them. Finally, you will discover how to use Selenium drivers with R for more sophisticated scraping. You will create AWS instances and use R to connect a PostgreSQL database hosted on AWS. By the end of the book, you will be sufficiently confident to create end-to-end web scraping systems using R. What you will learn Write and create regEX rules Write XPath rules to query your data Learn how web scraping methods work Use rvest to crawl web pages Store data retrieved from the web Learn the key uses of Rselenium to scrape data Who this book is for This book is for R programmers who want to get started quickly with web scraping, as well as data analysts who want to learn scraping using R. Basic knowledge of R is all you need to get started with this book.
    Note: Description based on online resource; title from title page (viewed January 9, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789138733/?ar
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  • 14
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    Git version control cookbook : leverage version control to transform your development workflow and boost productivity (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789136944 , 1789136946
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Git (Computer file) ; Software engineering ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: A series of practical recipes to simplify the Git learning experience and increase your productivity when using Git version control Key Features Explore practical recipes to use Git's most advanced features Learn how Git references its objects and how history is recorded Use reflog and git fsck to recover lost information Book Description Git is one of the most popular tools for versioning. Git Version Control Cookbook builds on the success of the previous edition and provides you with an up-to-date guide to solving problems related to versioning. You'll start by learning about the Git data model and how it stores files and looks at commits. By using simple commands, you'll learn how to navigate through the database. Once you have accustomed yourself to the basics, you'll explore techniques to configure Git with comprehensive examples and configuration targets. You'll gain insights into improving your understanding of branches and recovery from mistakes - right from committing to a wrong branch to recovering lost commits or files. You'll then move on to discovering the features that Git rebase has to offer and use regular Git merge on other branches. You'll explore Git notes and learn how to utilize the update, list, and search commands. In addition to this, you'll learn how to extract metadata from repositories and automate your daily tasks using Git hooks. You'll then study in detail repository maintenance, patching, and offline sharing. By the end of the book, you'll have grasped various tips and tricks for everyday usage, while increasing your knowledge of Git providers, integrations, and clients. What you will learn Understand the Git data model and use commands to navigate the database Find out how you can recover lost commits or files Force a rebase on some branches and use regular Git to merge on the rest Master the techniques required to extract metadata from repositories Explore Git notes and learn about the various features that it offers See how to decode different subcommands Who this book is for The Git Version Control Cookbook is for you if you are a developer or Build Release manager looking for a full-fledged practical guide that will take your Git knowledge to the next level. Basic knowledge of GNU tools and shell or bash scripting is needed. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased t...
    Note: Previous edition published: 2014. - Description based on online resource; title from title page (Safari, viewed August 30, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789137545/?ar
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  • 15
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    Hands-on predictive analytics with Python : master the complete predictive analytics process, from problem definition to model deployment (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789134544 , 1789134544
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Decision making ; Data processing ; Data mining ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Step-by-step guide to build high performing predictive applications Key Features Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Book Description Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming. What you will learn Get to grips with the main concepts and principles of predictive analytics Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Who this book is for This book is for data analysts, data scientists, data engineers, and Python developers who want to learn about predictive modeling and would like to implement predictive analytics solutions using Python's data stack. People from other backgrounds who would like to enter this excitin...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 26, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789138719/?ar
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  • 16
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    Kubernetes on AWS : deploy and manage production-ready Kubernetes clusters on AWS (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788392358 , 1788392353
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Amazon Web Services (Firm) ; Application software ; Development ; Cloud computing ; Virtual computer systems ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Learn to implement container orchestration on AWS with ease Key Features Leverage the power of Kubernetes on AWS to deploy highly scalable applications Provision Kubernetes clusters on Amazon EC2 environments Implement best practices to improve efficiency and security of Kubernetes on the cloud Book Description Docker containers promise to radicalize the way developers and operations build, deploy, and manage applications running on the cloud. Kubernetes provides the orchestration tools you need to realize that promise in production. Kubernetes on AWS guides you in deploying a production-ready Kubernetes cluster on the AWS platform. You will then discover how to utilize the power of Kubernetes, which is one of the fastest growing platforms for production-based container orchestration, to manage and update your applications. Kubernetes is becoming the go-to choice for production-grade deployments of cloud-native applications. This book covers Kubernetes from first principles. You will start by learning about Kubernetes' powerful abstractions - Pods and Services - that make managing container deployments easy. This will be followed by a guided tour through setting up a production-ready Kubernetes cluster on AWS, while learning the techniques you need to successfully deploy and manage your own applications. By the end of the book, you will have gained plenty of hands-on experience with Kubernetes on Amazon Web Services. You will also have picked up some tips on deploying and managing applications, keeping your cluster and applications secure, and ensuring that your whole system is reliable and resilient to failure. What you will learn Learn how to provision a production-ready Kubernetes cluster on AWS Deploy your own applications to Kubernetes with Helm Discover strategies for troubleshooting your cluster and know where to find help with issues Explore the best ways to monitor your cluster and the applications running on it Supercharge your cluster by integrating it with the tools provided by the AWS platform Architect your cluster for high availability Who this book is for If you're a cloud engineer, cloud solution provider, sysadmin, site reliability engineer, or developer with an interest in DevOps and are looking for an extensive guide to running Kubernetes in the AWS environment, this book is for you. Though any previous knowledge of Kubernetes is not expected, some experience with Linux and Docker containers would be a bonus.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 4, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788390071/?ar
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  • 17
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    Mastering Kubernetes : master the art of container management by using the power of Kubernetes (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788999977 , 1788999975
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition
    Parallel Title: Erscheint auch als
    Keywords: Linux ; Application software Development ; Virtual computer systems ; Cloud computing ; Open source software
    Note: Description based on online resource; title from title page (Safari, viewed May 31, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788999786/?ar
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  • 18
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    Beginning data analysis with Python and Jupyter : use powerful industry-standard tools to unlock new, actionable insight from your existing data (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789534658 , 1789534658
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Python (Computer program language) ; Information visualization ; Electronic data processing ; Data mining
    Note: Description based on online resource; title from cover (Safari, viewed July 18, 2018). - Includes index
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781789532029/?ar
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  • 19
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    PfSense 2.x cookbook : manage and maintain your network using pfSense (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789808087 , 1789808081
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Firewalls (Computer security) ; Software configuration management ; Open source software ; Cloud computing ; Security measures ; Electronic books ; Electronic books ; local
    Abstract: A practical, example-driven guide to configuring even the most advanced features of pfSense 2.x Key Features Build a high-availability fault-tolerant security system with pfSense 2.x Leverage the latest version of pfSense to secure your cloud environment A recipe-based guide that will help you enhance your on-premise and cloud security principles Book Description pfSense is an open source distribution of the FreeBSD-based firewall that provides a platform for ?exible and powerful routing and firewalling. The versatility of pfSense presents us with a wide array of configuration options, which makes determining requirements a little more difficult and a lot more important compared to other offerings. pfSense 2.x Cookbook ? Second Edition starts by providing you with an understanding of how to complete the basic steps needed to render a pfSense firewall operational. It starts by showing you how to set up different forms of NAT entries and firewall rules and use aliases and scheduling in firewall rules. Moving on, you will learn how to implement a captive portal set up in different ways (no authentication, user manager authentication, and RADIUS authentication), as well as NTP and SNMP configuration. You will then learn how to set up a VPN tunnel with pfSense. The book then focuses on setting up traffic shaping with pfSense, using either the built-in traffic shaping wizard, custom ?oating rules, or Snort. Toward the end, you will set up multiple WAN interfaces, load balancing and failover groups, and a CARP failover group. You will also learn how to bridge interfaces, add static routing entries, and use dynamic routing protocols via third-party packages. What you will learn Configure the essential pfSense services (namely, DHCP, DNS, and DDNS) Create aliases, firewall rules, NAT port-forward rules, and rule schedules Create multiple WAN interfaces in load-balanced or failover configurations Configure firewall redundancy with a CARP firewall failover Configure backup/restoration and automatic configuration-file backup Configure some services and perform diagnostics with command-line utilities Who this book is for This book is intended for all levels of network administrators. If you are an advanced user of pfSense, then you can flip to a particular recipe and quickly accomplish the task at hand; if you are new to pfSense, on the other hand, you can work through the book chapter by chapter and learn all of the features of the system from the ground up.
    Note: Previous edition published: 2011. - Description based on online resource; title from title page (Safari, viewed February 18, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789806427/?ar
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  • 20
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    Moodle course design best practices : design and develop outstanding Moodle learning experiences (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789349603 , 1789349605
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Moodle ; Computer-assisted instruction ; Computer programs ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Fast-paced guide for designing effective Moodle courses; experiment with Moodle's features for free using MoodleCloud Key Features Apply principles of instructional design to create great Moodle learning experiences Enhance collaboration and spur creativity with Moodle Bring together instructional materials, social interaction, and student management functions in your courses Book Description Moodle is a leading virtual learning environment for your online course. This book incorporates the principles of instructional design, showing you how to apply them to your Moodle courses. With this guidance, you will develop and deploy better courses, content, and assessments than ever. This book will guide you as you learn how to build and incorporate many different types of course materials and dynamic activities. You will learn how to improve the structure and presentation of resources, activities, and assessments. All this will help you to create better for self-led courses, instructor-led courses, and courses for collaborative groups. The use of multimedia features to enhance your Moodle courses is also explained in this book. Our goal is to encourage creativity, and the free MoodleCloud hosting option is an ideal place for teachers, students, trainers, and administrators to jump in and play with all the new features, which include powerful new plug-ins, new resources, and activities. Moodle can be your sandbox as well as your castle of learning! With this book, you will build learning experiences that will last your learners' lifetimes. What you will learn Build a course structure that fits your goals Design a unique appearance Manage the resources and activities Tips for better organization of your course content Select and set up assessments Include effective instructional strategies Incorporate competency frameworks Run and archive webinars Motivate learners by incorporating badges Explore MoodleCloud Who this book is for If you create courses with Moodle, this book is for you. It can be used by teachers, instructors, training managers, Moodle administrators, instructional technologists, instructional designers, and e-learning entrepreneurs. Prior experience with Moodle will be helpful.
    Note: Description based on online resource; title from title page (viewed September 12, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789348606/?ar
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  • 21
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    Docker quick start guide : learn Docker like a boss, and finally own your applications (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789341317 , 1789341310
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Open source software ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Develop and build your Docker images and deploy your Docker containers securely. Key Features Learn Docker installation on different types of OS Get started with developing Docker images Use Docker with your Jenkins CI/CD system Book Description Docker is an open source software platform that helps you with creating, deploying, and running your applications using containers. This book is your ideal introduction to Docker and containerization. You will learn how to set up a Docker development environment on a Linux, Mac, or Windows workstation, and learn your way around all the commands to run and manage your Docker images and containers. You will explore the Dockerfile and learn how to build your own enterprise-grade Docker images. Then you will learn about Docker networks, Docker swarm, and Docker volumes, and how to use these features with Docker stacks in order to define, deploy, and maintain highly-scalable, fault-tolerant multi-container applications. Finally, you will learn how to leverage Docker with Jenkins to automate the building of Docker images and the deployment of Docker containers. By the end of this book, you will be well prepared when it comes to using Docker for your next project. What you will learn Set up your Docker workstation on various platforms Utilize a number of Docker commands with parameters Create Docker images using Dockerfiles Learn how to create and use Docker volumes Deploy multi-node Docker swarm infrastructure Create and use Docker local and remote networks Deploy multi-container applications that are HA and FT Use Jenkins to build and deploy Docker images Who this book is for This guide is for anyone who needs to make a quick decision about using Docker for their next project. It is for developers who want to get started using Docker right away.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 14, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789347326/?ar
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  • 22
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    Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788830126 , 1788830121
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Big data ; Data mining ; Automatic data collection systems ; Electronic books ; Electronic books ; local
    Abstract: Transform machine data into powerful analytical intelligence using Splunk About This Book Analyze and visualize machine data to step into the world of Splunk! Leverage the exceptional analysis and visualization capabilities to make informed decisions for your business This easy-to-follow, practical book can be used by anyone - even if you have never managed data before Who This Book Is For This book is for the beginners who want to get well versed in the services offered by Splunk 7. If you want to be a data/business analyst or want to be a system administrator, this book is what you want. No prior knowledge of Splunk is required. What You Will Learn Install and configure Splunk for personal use Store event data in Splunk indexes, classify events into sources, and add data fields Learn essential Splunk Search Processing Language commands and best practices Create powerful real-time or user-input dashboards Be proactive by implementing alerts and scheduled reports Tips from the Fez: best practices using Splunk features and add-ons Understand security and deployment considerations for taking Splunk to an organizational level In Detail Splunk is a search, reporting, and analytics software platform for machine data, which has an ever-growing market adoption rate. More organizations than ever are adopting Splunk to make informed decisions in areas such as IT operations, information security, and the Internet of Things. The first two chapters of the book will get you started with a simple Splunk installation and set up of a sample machine data generator, called Eventgen. After this, you will learn to create various reports, dashboards, and alerts. You will also explore Splunk's Pivot functionality to model data for business users. You will then have the opportunity to test-drive Splunk's powerful HTTP Event Collector. After covering the core Splunk functionality, you'll be provided with some real-world best practices for using Splunk, and information on how to build upon what you've learned in this book. Throughout the book, there will be additional comments and best practice recommendations from a member of the SplunkTrust Community, called "Tips from the Fez". Style and approach This fast-paced, example-rich guide will help you analyze and visualize machine data with Splunk through simple, practical instructions and recommendations. Downloading the example code for this book You can download the example code files for all Packt books you have purc...
    Note: Description based on online resource; title from title page (Safari, viewed April 30, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788839112/?ar
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  • 23
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    Kubernetes cookbook : practical solutions to container orchestration (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788836876 , 1788836871
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Linux ; Application software ; Development ; Virtual computer systems ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Learn how to automate and manage your containers and reduce the overall operation burden on your system. About This Book Use containers to manage, scale and orchestrate apps in your organization Transform the latest concept of Kubernetes 1.10 into examples Expert techniques for orchestrating containers effectively Who This Book Is For This book is for system administrators, developers, DevOps engineers, or any stakeholder who wants to understand how Kubernetes works using a recipe-based approach. Basic knowledge of Kubernetes and Containers is required. What You Will Learn Build your own container cluster Deploy and manage highly scalable, containerized applications with Kubernetes Build high-availability Kubernetes clusters Build a continuous delivery pipeline for your application Track metrics and logs for every container running in your cluster Streamline the way you deploy and manage your applications with large-scale container orchestration In Detail Kubernetes is an open source orchestration platform to manage containers in a cluster environment. With Kubernetes, you can configure and deploy containerized applications easily. This book gives you a quick brush up on how Kubernetes works with containers, and an overview of main Kubernetes concepts, such as Pods, Deployments, Services and etc. This book explains how to create Kubernetes clusters and run applications with proper authentication and authorization configurations. With real-world recipes, you'll learn how to create high availability Kubernetes clusters on AWS, GCP and in on-premise datacenters with proper logging and monitoring setup. You'll also learn some useful tips about how to build a continuous delivery pipeline for your application. Upon completion of this book, you will be able to use Kubernetes in production and will have a better understanding of how to manage containers using Kubernetes. Style and approach This recipe-based book will teach you how to use Kubernetes in production and will help you discover various steps involved in managing your containers using Kubernetes Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Previous edition published: 2016. - Description based on online resource; title from title page (Safari, viewed July 31, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788837606/?ar
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  • 24
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    Mastering Apache Solr 7.x : an expert guide to advancing, optimizing, and scaling your enterprise search (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788831550 , 1788831551
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Apache Solr ; Search engines ; Programming ; Web search engines ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Accelerate your enterprise search engine and bring relevancy in your search analytics About This Book A practical guide in building expertise with Indexing, Faceting, Clustering and Pagination Master the management and administration of Enterprise Search Applications and services seamlessly Handle multiple data inputs such as JSON, xml, pdf, doc, xls,ppt, csv and much more. Who This Book Is For The book would rightly appeal to developers, software engineers, data engineers and database architects who are building or seeking to build enterprise-wide effective search engines for business intelligence. Prior experience of Apache Solr or Java programming is must to take the best of this book. What You Will Learn Design schema using schema API to access data in the database Advance querying and fine-tuning techniques for better performance Get to grips with indexing using Client API Set up a fault tolerant and highly available server with newer distributed capabilities, SolrCloud Explore Apache Tika to upload data with Solr Cell Understand different data operations that can be done while indexing Master advanced querying through Velocity Search UI, faceting and Query Re-ranking, pagination and spatial search Learn to use JavaScript, Python, SolrJ and Ruby for interacting with Solr In Detail Apache Solr is the only standalone enterprise search server with a REST-like application interface. providing highly scalable, distributed search and index replication for many of the world's largest internet sites. To begin with, you would be introduced to how you perform full text search, multiple filter search, perform dynamic clustering and so on helping you to brush up the basics of Apache Solr. You will also explore the new features and advanced options released in Apache Solr 7.x which will get you numerous performance aspects and making data investigation simpler, easier and powerful. You will learn to build complex queries, extensive filters and how are they compiled in your system to bring relevance in your search tools. You will learn to carry out Solr scoring, elements affecting the document score and how you can optimize or tune the score for the application at hand. You will learn to extract features of documents, writing complex queries in re-ranking the documents. You will also learn advanced options helping you to know what content is indexed and how the extracted content is indexed. Throughout the book, you would go through complex problems wi...
    Note: Description based on online resource; title from title page (Safari, viewed March 9, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788837385/?ar
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  • 25
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    Docker for serverless applications : containerize and orchestrate functions using OpenFaas, OpenWhisk, and Fn (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788837576 , 1788837576
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Application software ; Development ; Computer software ; Development ; Computer architecture ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Build applications and infrastructures that leverage Function-as-a-Service and Docker About This Book Implement containerization in Serverless/FaaS environments Utilize Docker as a functional unit of work for Serverless/FaaS platforms Use Docker as a portable infrastructure for Serverless Applications Who This Book Is For If you are a Developer, a Docker Engineer, a DevOps Engineer, or any stakeholder interested in learning the use of Docker on Serverless environments then this book is for you. What You Will Learn Learn what Serverless and FaaS applications are Get acquainted with the architectures of three major serverless systems Explore how Docker technologies can help develop Serverless applications Create and maintain FaaS infrastructures Set up Docker infrastructures to serve as on-premises FaaS infrastructures Define functions for Serverless applications with Docker containers In Detail Serverless applications have gained a lot of popularity among developers and are currently the buzzwords in the tech market. Docker and serverless are two terms that go hand-in-hand. This book will start by explaining serverless and Function-as-a-Service (FaaS) concepts, and why they are important. Then, it will introduce the concepts of containerization and how Docker fits into the Serverless ideology. It will explore the architectures and components of three major Docker-based FaaS platforms, how to deploy and how to use their CLI. Then, this book will discuss how to set up and operate a production-grade Docker cluster. We will cover all concepts of FaaS frameworks with practical use cases, followed by deploying and orchestrating these serverless systems using Docker. Finally, we will also explore advanced topics and prototypes for FaaS architectures in the last chapter. By the end of this book, you will be in a position to build and deploy your own FaaS platform using Docker. Style and approach A practical guide that offers a simple way to easily understand Serverless Applications utilizing Docker as the development environment.
    Note: Description based on online resource; title from title page (Safari, viewed May 21, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788835268/?ar
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    Docker cookbook : over 100 practical and insightful recipes to build distributed applications with Docker (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788625982 , 1788625986
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Linux ; Computer networks ; Management ; Open source software ; Virtual computer systems ; Electronic books ; Electronic books ; local
    Abstract: Leverage Docker to deploying software at scale Key Features Leverage practical examples to manage containers efficiently Integrate with orchestration tools such as Kubernetes for controlled deployments Learn to implement best practices on improving efficiency and security of containers Book Description Docker is an open source platform for building, shipping, managing, and securing containers. Docker has become the tool of choice for people willing to work with containers. Since the market is moving toward containerization, Docker will definitely have a big role to play in the future tech market. This book starts with setting up Docker in different environment, and helps you learn how to work with Docker images. Then, you will take a deep dive into network and data management for containers. The book explores the RESTful APIs provided by Docker to perform different actions, such as image/container operations. The book then explores logs and troubleshooting Docker to solve issues and bottlenecks. You will gain an understanding of Docker use cases, orchestration, security, ecosystems, and hosting platforms to make your applications easy to deploy, build, and collaborate on. The book covers the new features of Docker 18.xx (or later), such as working with AWS and Azure, Docker Engine, Docker Swarm, Docker Compose, and so on. By the end of this book, you will have gained hands-on experience of finding quick solutions to different problems encountered while working with Docker. What you will learn Install Docker on various platforms Work with Docker images and containers Container networking and data sharing Docker APIs and language bindings Various PaaS solutions for Docker Implement container orchestration using Docker Swarm and Kubernetes Container security Docker on various clouds Who this book is for Book is targeted towards developers, system administrators, and DevOps engineers who want to use Docker in his/her development, QA, or production environments. It is expected that the reader has basic Linux/Unix skills such as installing packages, editing files, managing services, and so on. Any experience in virtualization technologies such as KVM, XEN, and VMware will be an added advantage Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and regi...
    Note: Previous edition published: 2015. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed October 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788626866/?ar
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  • 27
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    Hands-on big data modeling : effective database design techniques for data architects and business intelligence professionals (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788626088 , 1788626087
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Database design ; Big data ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Solve all big data problems by learning how to create efficient data models Key Features Create effective models that get the most out of big data Apply your knowledge to datasets from Twitter and weather data to learn big data Tackle different data modeling challenges with expert techniques presented in this book Book Description Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you'll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you'll work with structured and semi-structured data with the help of real-life examples. Once you've got to grips with the basics, you'll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You'll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you'll be able to design and develop efficient data models for varying data sizes easily and efficiently. What you will learn Get insights into big data and discover various data models Explore conceptual, logical, and big data models Understand how to model data containing different file types Run through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modeling Create data models such as Graph Data and Vector Space Model structured and unstructured data using Python and R Who this book is for This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 4, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788620901/?ar
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  • 28
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    OpenStack cloud computing cookbook : over 100 practical recipes to help you build and operate OpenStack cloud computing, storage, networking, and automation (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788399333 , 1788399331
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Fourth edition.
    Keywords: OpenStack ; Open source software ; Cloud computing ; Electronic books ; Electronic books ; local
    Abstract: The Fourth Edition of the industry-acclaimed OpenStack Cloud Computing Cookbook, from four recognized experts, updated to the latest OpenStack build including Cinder, Nova, and Neutron. About This Book Over 100 recipes created by a team of OpenStack experts Updated to work with the latest OpenStack builds, with recipes covering the installation and use of OpenStack with Ansible It covers topics such as Keystone, Glance, Neutron, Nova, Cinder, and more, plus recipes for OpenStack storage, networking, and orchestrating workloads Test drive OpenStack using the accompanying Vagrant environment Who This Book Is For This book is written for cloud system engineers, system administrators, and technical architects who are moving from a virtualized environment to cloud environments. This book assumes that you are familiar with cloud computing platforms, and have knowledge of virtualization, networking, and managing Linux environments. What You Will Learn Understand, install, configure, and manage a complete OpenStack Cloud platform using OpenStack-Ansible Configure networks, routers, load balancers, and more with Neutron Use Keystone to setup domains, roles, groups and user access Learn how to use Swift and setup container access control lists Gain hands-on experience and familiarity with Horizon, the OpenStack Dashboard user interface Automate complete solutions with our recipes on Heat, the OpenStack Orchestration service as well as using Ansible to orchestrate application workloads Follow practical advice and examples to run OpenStack in production In Detail This is the fourth edition of the industry-acclaimed OpenStack Cloud Computing Cookbook, created by four recognized OpenStack experts. It has now been updated to work with the latest OpenStack builds, using tools and processes based on their collective and vast OpenStack experience. OpenStack Open Source Cloud software is one of the most used cloud infrastructures to support a wide variety of use cases, from software development to big data analysis. It is developed by a thriving community of individual developers from around the globe and backed by most of the leading players in the cloud space today. We make it simple to implement, massively scalable, and able to store a large pool of data and networking resources. OpenStack has a strong ecosystem that helps you provision your cloud storage needs. Add OpenStack's enterprise features to reduce the cost of your business. This book will begin by s...
    Note: Includes index. - Description based on online resource; title from cover (viewed February 21, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788398763/?ar
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  • 29
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    CMake cookbook : building, testing, and packaging modular software with modern CMake (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788472340 , 1788472349
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: CMake (Computer program) ; C++ (Computer program language) ; Open source software ; Operating systems (Computers) ; Electronic books ; Electronic books ; local
    Abstract: Learn CMake through a series of task-based recipes that provide you with practical, simple, and ready-to-use CMake solutions for your code Key Features Learn to configure, build, test, and package software written in C, C++, and Fortran Progress from simple to advanced tasks with examples tested on Linux, macOS, and Windows Manage code complexity and library dependencies with reusable CMake building blocks Book Description CMake is cross-platform, open-source software for managing the build process in a portable fashion. This book features a collection of recipes and building blocks with tips and techniques for working with CMake, CTest, CPack, and CDash. CMake Cookbook includes real-world examples in the form of recipes that cover different ways to structure, configure, build, and test small- to large-scale code projects. You will learn to use CMake's command-line tools and master modern CMake practices for configuring, building, and testing binaries and libraries. With this book, you will be able to work with external libraries and structure your own projects in a modular and reusable way. You will be well-equipped to generate native build scripts for Linux, MacOS, and Windows, simplify and refactor projects using CMake, and port projects to CMake. What you will learn Configure, build, test, and install code projects using CMake Detect operating systems, processors, libraries, files, and programs for conditional compilation Increase the portability of your code Refactor a large codebase into modules with the help of CMake Build multi-language projects Know where and how to tweak CMake configuration files written by somebody else Package projects for distribution Port projects to CMake Who this book is for If you are a software developer keen to manage build systems using CMake or would like to understand and modify CMake code written by others, this book is for you. A basic knowledge of C++, C, or Fortran is required to understand the topics covered in this book. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Description based on online resource; title from title page (Safari, viewed November 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788470711/?ar
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  • 30
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    OpenStack for architects : design production-ready private cloud infrastructure (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788628150 , 1788628152
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition
    Parallel Title: Erscheint auch als
    Keywords: OpenStack (Electronic resource) ; Cloud computing ; Computing platforms ; Open source software
    Note: Description based on online resource; title from title page (Safari, viewed June 27, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788624510/?ar
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  • 31
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    R deep learning projects : master the techniques to design and develop neural network models in R (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788474559 , 1788474554
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Machine learning ; R (Computer program language) ; Data mining
    Note: Description based on online resource; title from title page (viewed March 14, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788478403/?ar
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  • 32
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    Splunk operational intelligence cookbook : over 80 recipes for transforming your data into business-critical insights using Splunk (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788833080 , 1788833082
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition
    Parallel Title: Erscheint auch als
    RVK:
    ST 530
    Keywords: Big data ; Data mining ; Automatic data collection systems
    Note: Description based on online resource; title from title page (Safari, viewed June 29, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788835237/?ar
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  • 33
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    Apache Spark 2 data processing and real-time analytics : master complex big data processing, stream analytics, and machine learning with Apache (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789959918 , 1789959918
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Data mining ; Big data ; Machine learning ; Electronic data processing ; Electronic books ; Electronic books ; local
    Abstract: Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework Key Features Master the art of real-time big data processing and machine learning Explore a wide range of use-cases to analyze large data Discover ways to optimize your work by using many features of Spark 2.x and Scala Book Description Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: Mastering Apache Spark 2.x by Romeo Kienzler Scala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla Apache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook What you will learn Get to grips with all the features of Apache Spark 2.x Perform highly optimized real-time big data processing Use ML and DL techniques with Spark MLlib and third-party tools Analyze structured and unstructured data using SparkSQL and GraphX Understand tuning, debugging, and monitoring of big data applications Build scalable and fault-tolerant streaming applications Develop scalable recommendation engines Who this book is for If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.
    Note: Description based on online resource; title from title page (Safari, viewed March 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789959208/?ar
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    Hands-on data science with R : techniques to perform data manipulation and mining to build smart analytical models using R (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789135831 , 1789135834
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: R (Computer program language) ; Mathematical statistics ; Data processing ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: A hands-on guide for professionals to perform various data science tasks in R Key Features Explore the popular R packages for data science Use R for efficient data mining, text analytics and feature engineering Become a thorough data science professional with the help of hands-on examples and use-cases in R Book Description R is the most widely used programming language, and when used in association with data science, this powerful combination will solve the complexities involved with unstructured datasets in the real world. This book covers the entire data science ecosystem for aspiring data scientists, right from zero to a level where you are confident enough to get hands-on with real-world data science problems. The book starts with an introduction to data science and introduces readers to popular R libraries for executing data science routine tasks. This book covers all the important processes in data science such as data gathering, cleaning data, and then uncovering patterns from it. You will explore algorithms such as machine learning algorithms, predictive analytical models, and finally deep learning algorithms. You will learn to run the most powerful visualization packages available in R so as to ensure that you can easily derive insights from your data. Towards the end, you will also learn how to integrate R with Spark and Hadoop and perform large-scale data analytics without much complexity. What you will learn Understand the R programming language and its ecosystem of packages for data science Obtain and clean your data before processing Master essential exploratory techniques for summarizing data Examine various machine learning prediction, models Explore the H2O analytics platform in R for deep learning Apply data mining techniques to available datasets Work with interactive visualization packages in R Integrate R with Spark and Hadoop for large-scale data analytics Who this book is for If you are a budding data scientist keen to learn about the popular pandas library, or a Python developer looking to step into the world of data analysis, this book is the ideal resource you need to get started. Some programming experience in Python will be helpful to get the most out of this course
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 1, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789139402/?ar
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  • 35
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    Getting started with Kubernetes : extend your containerization strategy by orchestrating and managing large-scale container deployments (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788997263 , 1788997263
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Linux ; Application software ; Development ; Virtual computer systems ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Schedule and run application containers using Kubernetes Key Features Get to grips with a wide range of tools to monitor and secure your deployments Manage your container clusters and networks using Kubernetes Get well-versed with the fundamentals of Kubernetes Book Description Kubernetes has continued to grow and achieve broad adoption across various industries, helping you to orchestrate and automate container deployments on a massive scale. Based on the recent release of Kubernetes 1.12, Getting Started with Kubernetes gives you a complete understanding of how to install a Kubernetes cluster. The book focuses on core Kubernetes constructs, such as pods, services, replica sets, replication controllers, and labels. You will understand cluster-level networking in Kubernetes, and learn to set up external access to applications running in the cluster. As you make your way through the book, you'll understand how to manage deployments and perform updates with minimal downtime. In addition to this, you will explore operational aspects of Kubernetes , such as monitoring and logging, later moving on to advanced concepts such as container security and cluster federation. You'll get to grips with integrating your build pipeline and deployments within a Kubernetes cluster, and be able to understand and interact with open source projects. In the concluding chapters, you'll orchestrate updates behind the scenes, avoid downtime on your cluster, and deal with underlying cloud provider instability within your cluster. By the end of this book, you'll have a complete understanding of the Kubernetes platform and will start deploying applications on it. What you will learn Download, install, and configure the Kubernetes code base Set up and access monitoring and logging for Kubernetes clusters Set up external access to applications running in the cluster Learn how to manage and scale kubernetes with hosted platforms on AWS, Azure, and GCP Run multiple clusters and manage them from a single control plane Discover top tools for deploying and managing a Kubernetes cluster Learn how to get production ready and harden Kubernetes operations, networking, and storage Who this book is for Getting Started with Kubernetes is for developers, system administrators, and DevOps engineers who want to automate the deployment process and scale their applications. No prior knowledge of Kubernetes is required.
    Note: Description based on online resource; title from title page (viewed January 7, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788994729/?ar
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    Mastering Qlik Sense : expert techniques on self-service data analytics to create enterprise ready business intelligence solutions (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781782174875 , 1782174877
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Management information systems ; Business intelligence ; Computer programs ; Information visualization ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Master the capabilities of Qlik Sense to design and deploy solutions that address all the Business Intelligence needs of your organization About This Book Create compelling dashboards and visualizations with your data by leveraging Qlik Sense's self-service model Perform data loading and model efficient solutions with faster performance and better governance Master Qlik Sense's APIs and develop powerful mashups and fantastic extensions for visualizations and other components that run across all platforms Who This Book Is For This book is for Business Intelligence professionals and Data Analysts who want to become experts in using Qlik Sense. If you have extensively used QlikView in the past and are looking to transition to Qlik Sense, this book will also help you. A fundamental understanding of how Qlik Sense works and its features is all you need to get started with this book. What You Will Learn Understand the importance of self-service analytics and the IKEA-effect Explore all the available data modeling techniques and create efficient and optimized data models Master security rules and translate permission requirements into security rule logic Familiarize yourself with different types of Master Key Item(MKI) and know how and when to use MKI. Script and write sophisticated ETL code within Qlik Sense to facilitate all data modeling and data loading techniques Get an extensive overview of which APIs are available in Qlik Sense and how to take advantage of a technology with an API Develop basic mashup HTML pages and deploy successful mashup projects In Detail Qlik Sense is a powerful, self-servicing Business Intelligence tool for data discovery, analytics and visualization. It allows you to create personalized Business Intelligence solutions from raw data and get actionable insights from it. This book is your one-stop guide to mastering Qlik Sense, catering to all your organizational BI needs. You'll see how you can seamlessly navigate through tons of data from multiple sources and take advantage of the various APIs available in Qlik and its components for guided analytics. You'll also learn how to embed visualizations into your existing BI solutions and extend the capabilities of Qlik Sense to create new visualizations and dashboards that work across all platforms. We also cover other advanced concepts such as porting your Qlik View applications to Qlik Sense,and working with Qlik Cloud. Finally, you'll implement enterprise-wide security and ...
    Note: Description based on online resource; title from title page (viewed March 30, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781783554027/?ar
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    TensorFlow : powerful predictive analytics with TensorFlow : predict valuable insights of your data with TensorFlow (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789130423 , 1789130425
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Data mining ; Big data ; Decision making Data processing ; Application software Development ; Machine learning
    Note: Description based on online resource; title from cover (Safari, viewed April 3, 2018). - "Rapid learning solution."
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781789136913/?ar
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  • 38
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    Numerical computing with Python : harness the power of Python to analyze and find hidden patterns in the data (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789957228 , 1789957222
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Data mining ; Information visualization ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Understand, explore, and effectively present data using the powerful data visualization techniques of Python Key Features Use the power of Pandas and Matplotlib to easily solve data mining issues Understand the basics of statistics to build powerful predictive data models Grasp data mining concepts with helpful use-cases and examples Book Description Data mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining. You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models. By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional. This Learning Path includes content from the following Packt products: Statistics for Machine Learning by Pratap Dangeti Matplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin Yim Pandas Cookbook by Theodore Petrou What you will learn Understand the statistical fundamentals to build data models Split data into independent groups Apply aggregations and transformations to each group Create impressive data visualizations Prepare your data and design models Clean up data to ease data analysis and visualization Create insightful visualizations with Matplotlib and Seaborn Customize the model to suit your own predictive goals Who this book is for If you want to learn how to use the many libraries of Python to extract impactful information from your data and present it as engaging visuals, then this is the ideal Learning Path for you. Some basic knowledge of Python is enough to get started with this Learning Path.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 20, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789953633/?ar
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    Learning Jupyter 5 : explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789137446 , 1789137446
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Science ; Data processing ; Data mining ; Information visualization ; Python (Computer program language) ; Java (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Create and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter Key Features Learn how to use Jupyter 5.x features such as cell tagging and attractive table styles Leverage big data tools and datasets with different Python packages Explore multiple-user Jupyter Notebook servers Book Description The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode. By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you've explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization. What you will learn Install and run the Jupyter Notebook system on your machine Implement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook Use interactive widgets to manipulate and visualize data in real time Start sharing your Notebook with colleagues Invite your colleagues to work with you on the same Notebook Organize your Notebook using Jupyter namespaces Access big data in Jupyter for dealing with large datasets using Spark Who this book is for Learning Jupyter 5 is for developers, data scientists, machine learning users, and anyone working on data analysis or data science projects across different teams. Data science professionals will also find this book useful for performing technical and scientific computing collaboratively. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If ...
    Note: Previous edition published: 2016. - Description based on online resource; title from title page (Safari, viewed October 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789137408/?ar
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    Jupyter cookbook : over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788839747 , 1788839749
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    RVK:
    ST 232
    Keywords: Electronic data processing ; Data mining ; Information visualization ; Python (Computer program language) ; R (Computer program language) ; Scala (Computer program language)
    Note: Description based on online resource; title from title page (Safari, viewed May 31, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: lizenzpflichtig
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    Implementing Splunk 7 : effective operational intelligence to transform machine-generated data into valuable business insight (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788830508 , 1788830504
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition
    Parallel Title: Erscheint auch als
    Keywords: Big data Data processing ; Data mining ; Automatic data collection systems
    Note: Description based on online resource; title from title page (Safari, viewed May 3, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788836289/?ar
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    Learn Docker : fundamentals of Docker 18.x : everything you need to know about containerizing your applications and running them in production (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788995795 , 1788995791
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    RVK:
    ST 230
    RVK:
    ST 232
    Keywords: Application software Development ; Computer software Development ; Computer architecture ; Open source software ; Docker ; Docker
    Note: Description based on online resource; title from title page (Safari, viewed May 23, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788997027/?ar
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  • 43
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    Extending OpenStack : leverage extended OpenStack projects to implement containerization, deployment, and architecting robust cloud solutions (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786466136 , 1786466139
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Cloud computing ; Information technology Management ; Open source software
    Note: Description based on online resource; title from title page (viewed March 30, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781786465535/?ar
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  • 44
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    Hands-on recommendation systems with Python : start building powerful and personalized, recommendation engines with Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788992534 , 1788992539
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Internet marketing ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web Key Features Build industry-standard recommender systems Only familiarity with Python is required No need to wade through complicated machine learning theory to use this book Book Description Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform. This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory - you'll get started with building and learning about recommenders as quickly as possible.. In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains. What you will learn Get to grips with the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content based engine to recommend movies based on movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative fltering Who this book is for If you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory.
    Note: Description based on online resource; title from title page (Safari, viewed August 27, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788993753/?ar
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    Hands-on full stack web development with ASP.NET Core : learn end-to-end web development with leading frontend frameworks, such as Angular, React, and Vue (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788627757 , 178862775X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Software frameworks ; Web applications ; Development ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Become a full-stack developer by learning popular Microsoft technologies and platforms such as .NET Core, ASP.NET Core, Entity Framework, and Azure Key Features Bring static typing to web development with features compatible in TypeScript 3 Implement a slim marketplace single page application (SPA) in Angular, React, and Vue Modernize your web apps with Microsoft Azure, Visual Studio, and Git Book Description Today, full-stack development is the name of the game. Developers who can build complete solutions, including both backend and frontend products, are in great demand in the industry, hence being able to do so a desirable skill. However, embarking on the path to becoming a modern full-stack developer can be overwhelmingly difficult, so the key purpose of this book is to simplify and ease the process. This comprehensive guide will take you through the journey of becoming a full-stack developer in the realm of the web and .NET. It begins by implementing data-oriented RESTful APIs, leveraging ASP.NET Core and Entity Framework. Afterward, it describes the web development field, including its history and future horizons. Then, you'll build webbased Single-Page Applications (SPAs) by learning about numerous popular technologies, namely TypeScript, Angular, React, and Vue. After that, you'll learn about additional related concerns involving deployment, hosting, and monitoring by leveraging the cloud; specifically, Azure. By the end of this book, you'll be able to build, deploy, and monitor cloud-based, data-oriented, RESTful APIs, as well as modern web apps, using the most popular frameworks and technologies. What you will learn Build RESTful APIs in C# with ASP.NET Core, web APIs, and Entity Framework See the history and future horizons of the web development field Bring static-typing to web apps using TypeScript Build web applications using Angular, React, and Vue Deploy your application to the cloud Write web applications that scale, can adapt to changes, and are easy to maintain Discover best practices and real-world tips and tricks Secure your backend server with Authentication and Authorization using OAuth 2.0 Who this book is for This book is for developers who are keen on strengthening their skills in the field of cloud-based full-stack web development. You need basic knowledge of web-related pillars, including HTML, CSS, and JavaScript, as well as C# and REST. This book targets novice developers in the realm of Web development and ASP.NE...
    Note: Description based on online resource; title from title page (viewed January 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788622882/?ar
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    IBM Watson projects : eight exciting projects that put artificial intelligence into practice for optimal business performance (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789346695 , 178934669X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Watson (Computer) ; Natural language processing (Computer science) ; Data mining ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Incorporate intelligence to your data-driven business insights and high accuracy business solutions Key Features Explore IBM Watson capabilities such as Natural Language Processing (NLP) and machine learning Build projects to adopt IBM Watson across retail, banking, and healthcare Learn forecasting, anomaly detection, and pattern recognition with ML techniques Book Description IBM Watson provides fast, intelligent insight in ways that the human brain simply can't match. Through eight varied projects, this book will help you explore the computing and analytical capabilities of IBM Watson. The book begins by refreshing your knowledge of IBM Watson's basic data preparation capabilities, such as adding and exploring data to prepare it for being applied to models. The projects covered in this book can be developed for different industries, including banking, healthcare, media, and security. These projects will enable you to develop an AI mindset and guide you in developing smart data-driven projects, including automating supply chains, analyzing sentiment in social media datasets, and developing personalized recommendations. By the end of this book, you'll have learned how to develop solutions for process automation, and you'll be able to make better data-driven decisions to deliver an excellent customer experience. What you will learn Build a smart dialog system with cognitive assistance solutions Design a text categorization model and perform sentiment analysis on social media datasets Develop a pattern recognition application and identify data irregularities smartly Analyze trip logs from a driving services company to determine profit Provide insights into an organization's supply chain data and processes Create personalized recommendations for retail chains and outlets Test forecasting effectiveness for better sales prediction strategies Who this book is for This book is for data scientists, AI engineers, NLP engineers, machine learning engineers, and data analysts who wish to build next-generation analytics applications. Basic familiarity with cognitive computing and sound knowledge of any programming language is all you need to understand the projects covered in this book.
    Note: Description based on online resource; title from title page (Safari, viewed December 3, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789343717/?ar
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    Mastering Kibana 6.x : visualize your Elastic Stack data with histograms, maps, charts, and graphs (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788834032 , 1788834038
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Information visualization ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Get to grips with Kibana and its advanced functions to create interactive visualizations and dashboards Key Features Explore visualizations and perform histograms, stats, and map analytics Unleash X-Pack and Timelion, and learn alerting, monitoring, and reporting features Manage dashboards with Beats and create machine learning jobs for faster analytics Book Description Kibana is one of the popular tools among data enthusiasts for slicing and dicing large datasets and uncovering Business Intelligence (BI) with the help of its rich and powerful visualizations. To begin with, Mastering Kibana 6.x quickly introduces you to the features of Kibana 6.x, before teaching you how to create smart dashboards in no time. You will explore metric analytics and graph exploration, followed by understanding how to quickly customize Kibana dashboards. In addition to this, you will learn advanced analytics such as maps, hits, and list analytics. All this will help you enhance your skills in running and comparing multiple queries and filters, influencing your data visualization skills at scale. With Kibana's Timelion feature, you can analyze time series data with histograms and stats analytics. By the end of this book, you will have created a speedy machine learning job using X-Pack capabilities. What you will learn Create unique dashboards with various intuitive data visualizations Visualize Timelion expressions with added histograms and stats analytics Integrate X-Pack with your Elastic Stack in simple steps Extract data from Elasticsearch for advanced analysis and anomaly detection using dashboards Build dashboards from web applications for application logs Create monitoring and alerting dashboards using Beats Who this book is for Mastering Kibana 6.x is for you if you are a big data engineer, DevOps engineer, or data scientist aspiring to go beyond data visualization at scale and gain maximum insights from their large datasets. Basic knowledge of Elasticstack will be an added advantage, although not mandatory.
    Note: Description based on online resource; title from title page (Safari, viewed August 29, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788831031/?ar
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    Pentaho data integration quick start guide : create ETL processes using Pentaho (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789342796 , 1789342791
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Data integration (Computer science) ; Data mining ; Decision support systems ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Get productive quickly with Pentaho Data Integration Key Features Take away the pain of starting with a complex and powerful system Simplify your data transformation and integration work Explore, transform, and validate your data with Pentaho Data Integration Book Description Pentaho Data Integration(PDI) is an intuitive and graphical environment packed with drag and drop design and powerful Extract-Transform-Load (ETL) capabilities. Given its power and flexibility, initial attempts to use the Pentaho Data Integration tool can be difficult or confusing. This book is the ideal solution. This book reduces your learning curve with PDI. It provides the guidance needed to make you productive, covering the main features of Pentaho Data Integration. It demonstrates the interactive features of the graphical designer, and takes you through the main ETL capabilities that the tool offers. By the end of the book, you will be able to use PDI for extracting, transforming, and loading the types of data you encounter on a daily basis. What you will learn Design, preview and run transformations in Spoon Run transformations using the Pan utility Understand how to obtain data from different types of files Connect to a database and explore it using the database explorer Understand how to transform data in a variety of ways Understand how to insert data into database tables Design and run jobs for sequencing tasks and sending emails Combine the execution of jobs and transformations Who this book is for This book is for software developers, business intelligence analysts, and others involved or interested in developing ETL solutions, or more generally, doing any kind of data manipulation.
    Note: Description based on online resource; title from title page (Safari, viewed October 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789343328/?ar
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    Splunk 7.x quick start guide : gain business data insights from operational intelligence (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789538021 , 1789538025
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Big data ; Data mining ; Automatic data collection systems ; Electronic data processing ; Electronic books ; Electronic books ; local
    Abstract: Learn how to architect, implement, and administer a complex Splunk Enterprise environment and extract valuable insights from business data. Key Features Understand the various components of Splunk and how they work together to provide a powerful Big Data analytics solution. Collect and index data from a wide variety of common machine data sources Design searches, reports, and dashboard visualizations to provide business data insights Book Description Splunk is a leading platform and solution for collecting, searching, and extracting value from ever increasing amounts of big data - and big data is eating the world! This book covers all the crucial Splunk topics and gives you the information and examples to get the immediate job done. You will find enough insights to support further research and use Splunk to suit any business environment or situation. Splunk 7.x Quick Start Guide gives you a thorough understanding of how Splunk works. You will learn about all the critical tasks for architecting, implementing, administering, and utilizing Splunk Enterprise to collect, store, retrieve, format, analyze, and visualize machine data. You will find step-by-step examples based on real-world experience and practical use cases that are applicable to all Splunk environments. There is a careful balance between adequate coverage of all the critical topics with short but relevant deep-dives into the configuration options and steps to carry out the day-to-day tasks that matter. By the end of the book, you will be a confident and proficient Splunk architect and administrator. What you will learn Design and implement a complex Splunk Enterprise solution Configure your Splunk environment to get machine data in and indexed Build searches to get and format data for analysis and visualization Build reports, dashboards, and alerts to deliver critical insights Create knowledge objects to enhance the value of your data Install Splunk apps to provide focused views into key technologies Monitor, troubleshoot, and manage your Splunk environment Who this book is for This book is intended for experienced IT personnel who are just getting started working with Splunk and want to quickly become proficient with its usage. Data analysts who need to leverage Splunk to extract critical business insights from application logs and other machine data sources will also benefit from this book.
    Note: Description based on online resource; title from title page (Safari, viewed February 14, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789531091/?ar
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    Become a Python data analyst : perform exploratory data analysis and gain insight into scientific computing using Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789534405 , 1789534402
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Data mining ; Python (Computer program language) ; Quantitative research ; Science ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Enhance your data analysis and predictive modeling skills using popular Python tools Key Features Cover all fundamental libraries for operation and manipulation of Python for data analysis Implement real-world datasets to perform predictive analytics with Python Access modern data analysis techniques and detailed code with scikit-learn and SciPy Book Description Python is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations. Become a Python Data Analyst introduces Python's most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations. In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques. By the end of this book, you will have hands-on experience performing data analysis with Python. What you will learn Explore important Python libraries and learn to install Anaconda distribution Understand the basics of NumPy Produce informative and useful visualizations for analyzing data Perform common statistical calculations Build predictive models and understand the principles of predictive analytics Who this book is for Become a Python Data Analyst is for entry-level data analysts, data engineers, and BI professionals who want to make complete use of Python tools for performing efficient data analysis. Prior knowledge of Python programming is necessary to understand the concepts covered in this book
    Note: Description based on online resource; title from title page (Safari, viewed October 2, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789531701/?ar
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    Learning data mining with Python : use Python to manipulate data and build predictive models (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787129566 , 178712956X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Harness the power of Python to develop data mining applications, analyze data, delve into machine learning, explore object detection using Deep Neural Networks, and create insightful predictive models. About This Book Use a wide variety of Python libraries for practical data mining purposes. Learn how to find, manipulate, analyze, and visualize data using Python. Step-by-step instructions on data mining techniques with Python that have real-world applications. Who This Book Is For If you are a Python programmer who wants to get started with data mining, then this book is for you. If you are a data analyst who wants to leverage the power of Python to perform data mining efficiently, this book will also help you. No previous experience with data mining is expected. What You Will Learn Apply data mining concepts to real-world problems Predict the outcome of sports matches based on past results Determine the author of a document based on their writing style Use APIs to download datasets from social media and other online services Find and extract good features from difficult datasets Create models that solve real-world problems Design and develop data mining applications using a variety of datasets Perform object detection in images using Deep Neural Networks Find meaningful insights from your data through intuitive visualizations Compute on big data, including real-time data from the internet In Detail This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations. Style and approach This book will be your comprehensive guide to learning the various data mining techniques and implementing them in Python. A variety of real-world datasets is used to explain data mining techniques in a very crisp...
    Note: Description based on online resource; title from title page (viewed May 16, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787126787/?ar
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    Learning Docker : faster app development and deployment with Docker containers (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786462015 , 178646201X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Linux ; Application software ; Development ; Computer software ; Development ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Docker lets you create, deploy, and manage your applications anywhere at anytime ? flexibility is key so you can deploy stable, secure, and scalable app containers across a wide variety of platforms and delve into microservices architecture About This Book This up-to-date edition shows how to leverage Docker's features to deploy your existing applications Learn how to package your applications with Docker and build, ship, and scale your containers Explore real-world examples of securing and managing Docker containers Who This Book Is For This book is ideal for developers, operations managers, and IT professionals who would like to learn about Docker and use it to build and deploy container-based apps. No prior knowledge of Docker is expected. What You Will Learn Develop containerized applications using the Docker version 17.03 Build Docker images from containers and launch them Develop Docker images and containers leveraging Dockerfiles Use Docker volumes to share data Get to know how data is shared between containers Understand Docker Jenkins integration Gain the power of container orchestration Familiarize yourself with the frequently used commands such as docker exec, docker ps, docker top, and docker stats In Detail Docker is an open source containerization engine that offers a simple and faster way for developing and running software. Docker containers wrap software in a complete filesystem that contains everything it needs to run, enabling any application to be run anywhere ? this flexibily and portabily means that you can run apps in the cloud, on virtual machines, or on dedicated servers. This book will give you a tour of the new features of Docker and help you get started with Docker by building and deploying a simple application. It will walk you through the commands required to manage Docker images and containers. You'll be shown how to download new images, run containers, list the containers running on the Docker host, and kill them. You'll learn how to leverage Docker's volumes feature to share data between the Docker host and its containers ? this data management feature is also useful for persistent data. This book also covers how to orchestrate containers using Docker compose, debug containers, and secure containers using the AppArmor and SELinux security modules. Style and approach This step-by-step guide will walk you through the features and use of Docker, from Docker software installation to the impenetrable security of con...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed June 23, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781786462923/?ar
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    FreeSWITCH 1.8 : VoIP and WebRTC with FreeSWITCH : the definitive source (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785888298 , 1785888293
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Internet telephony ; Computer network protocols ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Build a robust, high-performance telephony system with FreeSWITCH About This Book Learn how to install and configure a complete telephony system of your own, from scratch, using FreeSWITCH 1.6 Get in-depth discussions of important concepts such as dialplan, user directory, NAT handling, and the powerful FreeSWITCH event socket Discover expert tips from the FreeSWITCH experts, including the creator of FreeSWITCH-Anthony Minessale Who This Book Is For This book is for beginner-level IT professionals and enthusiasts who are interested in quickly getting a powerful telephony system up and running using FreeSWITCH. It would be good if you have some telephony experience, but it's not a must. What You Will Learn Build a complete WebRTC/SIP VoIP platform able to interconnect and process audio and video in real time Use advanced PBX features to create powerful dialplans Understand the inner workings and architecture of FreeSWITCH Real time configuration from database and webserver with mod_xml_curl Integrate browser clients into your telephony service Use scripting to go beyond the dialplan with the power and flexibility of a programming language Secure your FreeSWITCH connections with the help of effective techniques Deploy all FreeSWITCH features using best practices and expert tips Overcome frustrating NAT issues Control FreeSWITCH remotely with the all-powerful event socket Trace packets, check debug logging, ask for community and commercial help In Detail FreeSWITCH is an open source telephony platform designed to facilitate the creation of voice and chat-driven products, scaling from a soft-phone to a PBX and even up to an enterprise-class soft-switch. This book introduces FreeSWITCH to IT professionals who want to build their own telephony system. This book starts with a brief introduction to the latest version of FreeSWITCH. We then move on to the fundamentals and the new features added in version 1.6, showing you how to set up a basic system so you can make and receive phone calls, make calls between extensions, and utilize basic PBX functionality. Once you have a basic system in place, we'll show you how to add more and more functionalities to it. You'll learn to deploy the features on the system using unique techniques and tips to make it work better. Also, there are changes in the security-related components, which will affect the content in the book, so we will make that intact with the latest version. There are new support libraries intro...
    Note: Description based on online resource; title from title page (Safari, viewed August 4, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781785889134/?ar
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    Containerization with LXC : get acquainted with the world of LXC (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781783985685 , 1783985682
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Linux ; Abstract data types (Computer science) ; Application software ; Development ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Get acquainted with the world of LXC About This Book Get the most practical and up-to-date resource on LXC and take full advantage of what Linux containers can offer in the day-to-day operations of large-scale applications Learn how to deploy and administer various workloads such as web applications inside LXC Save your organization time and money by building robust and secure containers and by speeding the deployment process of your software Who This Book Is For This book is for Linux engineers and software developers who are looking to deploy applications in a fast, secure, and scalable way for use in testing and production. What You Will Learn Deep dive into the foundations of Linux containers with kernel namespaces and cgroups Install, configure, and administer Linux containers with LXC and libvirt Begin writing applications using Python libvirt bindings Take an in-depth look at container networking Set up monitoring and security with LXC Build and deploy a highly available application with LXC in the cloud In Detail In recent years, containers have gained wide adoption by businesses running a variety of application loads. This became possible largely due to the advent of kernel namespaces and better resource management with control groups (cgroups). Linux containers (LXC) are a direct implementation of those kernel features that provide operating system level virtualization without the overhead of a hypervisor layer. This book starts by introducing the foundational concepts behind the implementation of LXC, then moves into the practical aspects of installing and configuring LXC containers. Moving on, you will explore container networking, security, and backups. You will also learn how to deploy LXC with technologies like Open Stack and Vagrant. By the end of the book, you will have a solid grasp of how LXC is implemented and how to run production applications in a highly available and scalable way. Style and approach A practical guide that introduces the core technologies behind Linux containers and provides a deep dive into installation, configuration, and operations of LXC.
    Note: Description based on online resource; title from cover (viewed April 18, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781785888946/?ar
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    R : mining spatial, text, web, and social media data : create and customize data mioning algorithms : a course in three modules (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788290814 , 178829081X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Data mining ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Create data mining algorithms About This Book Develop a strong strategy to solve predictive modeling problems using the most popular data mining algorithms Real-world case studies will take you from novice to intermediate to apply data mining techniques Deploy cutting-edge sentiment analysis techniques to real-world social media data using R Who This Book Is For This Learning Path is for R developers who are looking to making a career in data analysis or data mining. Those who come across data mining problems of different complexities from web, text, numerical, political, and social media domains will find all information in this single learning path. What You Will Learn Discover how to manipulate data in R Get to know top classification algorithms written in R Explore solutions written in R based on R Hadoop projects Apply data management skills in handling large data sets Acquire knowledge about neural network concepts and their applications in data mining Create predictive models for classification, prediction, and recommendation Use various libraries on R CRAN for data mining Discover more about data potential, the pitfalls, and inferencial gotchas Gain an insight into the concepts of supervised and unsupervised learning Delve into exploratory data analysis Understand the minute details of sentiment analysis In Detail Data mining is the first step to understanding data and making sense of heaps of data. Properly mined data forms the basis of all data analysis and computing performed on it. This learning path will take you from the very basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining - social media mining. You will learn how to manipulate data with R using code snippets and how to mine frequent patterns, association, and correlation while working with R programs. You will discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on R Hadoop projects. Now that you are comfortable with data mining with R, you will move on to implementing your knowledge with the help of end-to-end data mining projects. You will learn how to apply different mining concepts to various statistical and data applications in a wide range of fields. At this stage, you will be able to complete complex data mining cases and handle any issues you might encounter during projects. After this, you will gain hands...
    Note: "Bater Makhabel, Pradeepta Mishra, Nathan Danneman, Richard Heimann."--Cover. - "Learning path"--Cover. - Includes bibliographical references and index. - Description based on online resource; title from title page (viewed July 6, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781788293747/?ar
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    Mastering OpenStack : discover your complete guide to designing, deploying, and managing OpenStack-based clouds in mid-to-large IT infrastructures with best practices, expert understanding, and more (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786462282 , 1786462281
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Cloud computing ; Information technology ; Management ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Discover your complete guide to designing, deploying, and managing OpenStack-based clouds in mid-to-large IT infrastructures with best practices, expert understanding, and more About This Book Design and deploy an OpenStack-based cloud in your mid-to-large IT infrastructure using automation tools and best practices Keep yourself up-to-date with valuable insights into OpenStack components and new services in the latest OpenStack release Discover how the new features in the latest OpenStack release can help your enterprise and infrastructure Who This Book Is For This book is for system administrators, cloud engineers, and system architects who would like to deploy an OpenStack-based cloud in a mid-to-large IT infrastructure. This book requires a moderate level of system administration and familiarity with cloud concepts. What You Will Learn Explore the main architecture design of OpenStack components and core-by-core services, and how they work together Design different high availability scenarios and plan for a no-single-point-of-failure environment Set up a multinode environment in production using orchestration tools Boost OpenStack's performance with advanced configuration Delve into various hypervisors and container technology supported by OpenStack Get familiar with deployment methods and discover use cases in a real production environment Adopt the DevOps style of automation while deploying and operating in an OpenStack environment Monitor the cloud infrastructure and make decisions on maintenance and performance improvement In Detail In this second edition, you will get to grips with the latest features of OpenStack. Starting with an overview of the OpenStack architecture, you'll see how to adopt the DevOps style of automation while deploying and operating in an OpenStack environment. We'll show you how to create your own OpenStack private cloud. Then you'll learn about various hypervisors and container technology supported by OpenStack. You'll get an understanding about the segregation of compute nodes based on reliability and availability needs. We'll cover various storage types in OpenStack and advanced networking aspects such as SDN and NFV. Next, you'll understand the OpenStack infrastructure from a cloud user point of view. Moving on, you'll develop troubleshooting skills, and get a comprehensive understanding of services such as high availability and failover in OpenStack. Finally, you will gain experience of running a centralized...
    Note: Description based on online resource; title from title page (Safari, viewed May 15, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781786463982/?ar
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    Learning Spark SQL : architect streaming analytics and machine learning solutions (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785887352 , 1785887351
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Data mining ; Big data ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Design, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book Learn about the design and implementation of streaming applications, machine learning pipelines, deep learning, and large-scale graph processing applications using Spark SQL APIs and Scala. Learn data exploration, data munging, and how to process structured and semi-structured data using real-world datasets and gain hands-on exposure to the issues and challenges of working with noisy and "dirty" real-world data. Understand design considerations for scalability and performance in web-scale Spark application architectures. Who This Book Is For If you are a developer, engineer, or an architect and want to learn how to use Apache Spark in a web-scale project, then this is the book for you. It is assumed that you have prior knowledge of SQL querying. A basic programming knowledge with Scala, Java, R, or Python is all you need to get started with this book. What You Will Learn Familiarize yourself with Spark SQL programming, including working with DataFrame/Dataset API and SQL Perform a series of hands-on exercises with different types of data sources, including CSV, JSON, Avro, MySQL, and MongoDB Perform data quality checks, data visualization, and basic statistical analysis tasks Perform data munging tasks on publically available datasets Learn how to use Spark SQL and Apache Kafka to build streaming applications Learn key performance-tuning tips and tricks in Spark SQL applications Learn key architectural components and patterns in large-scale Spark SQL applications In Detail In the past year, Apache Spark has been increasingly adopted for the development of distributed applications. Spark SQL APIs provide an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Hence, understanding the design and implementation best practices before you start your project will help you avoid these problems. This book gives an insight into the engineering practices used to design and build real-world, Spark-based applications. The book's hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL. It starts by familiarizing you with data exploration and data munging tasks using Spark SQL and Scala. Extensive code examples will help yo...
    Note: Description based on online resource; title from title page (viewed October 3, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781785888359/?ar
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    R data mining : implement data mining techniques through practical use cases and real-world datasets (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787129238 , 1787129233
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    RVK:
    ST 530
    Keywords: Data mining ; R (Computer program language) ; R ; Data Mining ; R ; Data Mining
    Note: Description based on online resource; title from title page (Safari, viewed January 9, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781787124462/?ar
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    MongoDB administrator's guide : over 100 practical recipes to efficiently maintain and administer your MongoDB solution (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787127180 , 1787127184
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: MongoDB. ; Object-oriented databases ; Open source software
    Note: Description based on online resource; title from title page (Safari, viewed November 15, 2017)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781787126480/?ar
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  • 60
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    Practical data wrangling : expert techniques for transforming your raw data into a valuable source for analytics (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787283671 , 1787283674
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Data mining ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Turn your noisy data into relevant, insight-ready information by leveraging the data wrangling techniques in Python and R About This Book This easy-to-follow guide takes you through every step of the data wrangling process in the best possible way Work with different types of datasets, and reshape the layout of your data to make it easier for analysis Get simple examples and real-life data wrangling solutions for data pre-processing Who This Book Is For If you are a data scientist, data analyst, or a statistician who wants to learn how to wrangle your data for analysis in the best possible manner, this book is for you. As this book covers both R and Python, some understanding of them will be beneficial. What You Will Learn Read a csv file into python and R, and print out some statistics on the data Gain knowledge of the data formats and programming structures involved in retrieving API data Make effective use of regular expressions in the data wrangling process Explore the tools and packages available to prepare numerical data for analysis Find out how to have better control over manipulating the structure of the data Create a dexterity to programmatically read, audit, correct, and shape data Write and complete programs to take in, format, and output data sets In Detail Around 80% of time in data analysis is spent on cleaning and preparing data for analysis. This is, however, an important task, and is a prerequisite to the rest of the data analysis workflow, including visualization, analysis and reporting. Python and R are considered a popular choice of tool for data analysis, and have packages that can be best used to manipulate different kinds of data, as per your requirements. This book will show you the different data wrangling techniques, and how you can leverage the power of Python and R packages to implement them. You'll start by understanding the data wrangling process and get a solid foundation to work with different types of data. You'll work with different data structures and acquire and parse data from various locations. You'll also see how to reshape the layout of data and manipulate, summarize, and join data sets. Finally, we conclude with a quick primer on accessing and processing data from databases, conducting data exploration, and storing and retrieving data quickly using databases. The book includes practical examples on each of these points using simple and real-world data sets to give you an easier understanding. By the en...
    Note: Description based on online resource; title from title page (Safari, viewed December 19, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787286139/?ar
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    Java data analysis : data mining, big data analysis, NoSQL, and data visualization (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787286405 , 1787286401
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Java (Computer program language) ; Data mining ; Information visualization ; Electronic data processing ; Relational databases ; Electronic books ; Electronic books ; local
    Abstract: Get the most out of the popular Java libraries and tools to perform efficient data analysis About This Book Get your basics right for data analysis with Java and make sense of your data through effective visualizations. Use various Java APIs and tools such as Rapidminer and WEKA for effective data analysis and machine learning. This is your companion to understanding and implementing a solid data analysis solution using Java Who This Book Is For If you are a student or Java developer or a budding data scientist who wishes to learn the fundamentals of data analysis and learn to perform data analysis with Java, this book is for you. Some familiarity with elementary statistics and relational databases will be helpful but is not mandatory, to get the most out of this book. A firm understanding of Java is required. What You Will Learn Develop Java programs that analyze data sets of nearly any size, including text Implement important machine learning algorithms such as regression, classification, and clustering Interface with and apply standard open source Java libraries and APIs to analyze and visualize data Process data from both relational and non-relational databases and from time-series data Employ Java tools to visualize data in various forms Understand multimedia data analysis algorithms and implement them in Java. In Detail Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks. This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you'll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression. In the process, you'll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs. By the end of this book, you will have a solid understanding of...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed October 31, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787285651/?ar
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    Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787289864 , 1787289869
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Storm (Electronic resource) ; Big data ; Data mining ; Electronic data processing ; Distributed processing ; Management ; Electronic books ; Electronic books ; local
    Abstract: A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to dep...
    Note: Description based on online resource; title from title page (Safari, viewed October 31, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787281202/?ar
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    Hands-on data science and Python machine learning : perform data mining and machine learning efficiently using Python and Spark (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787280229 , 1787280225
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Python (Computer program language) ; Machine learning ; Data mining ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book Take your first steps in the world of data science by understanding the tools and techniques of data analysis Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. What You Will Learn Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python Train efficient machine learning models using decision trees and random forests Visualize the results of your analysis using Python's Matplotlib library Use Apache Spark's MLlib package to perform machine learning on large datasets In Detail Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis. Style and approach This comprehen...
    Note: Description based on online resource; title from title page (Safari, viewed August 18, 2017)
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    Practical data science cookbook : practical recipes on data pre-processing, analysis and visualization using R and Python (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787129627
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Object-oriented programming (Computer science) ; Data mining ; Mathematical statistics ; Data processing ; Python (Computer program language) ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Over 85 recipes to help you complete real-world data science projects in R and Python About This Book Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data Get beyond the theory and implement real-world projects in data science using R and Python Easy-to-follow recipes will help you understand and implement the numerical computing concepts Who This Book Is For If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python. What You Will Learn Learn and understand the installation procedure and environment required for R and Python on various platforms Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python Build a predictive model and an exploratory model Analyze the results of your model and create reports on the acquired data Build various tree-based methods and Build random forest In Detail As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis-R and Python. Style and approach This step-by-step guide to data science is full of hands-on examples of real-world data science tasks. Each recipe focuses on a particular task involved in the data science pipeline, ranging from readying the dataset to analytics and visualization Downloa...
    Note: Previous edition published: 2014. - Description based on online resource; title from title page (Safari, viewed July 26, 2017)
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    Learning social media analytics with R : transform data from social media platforms into actionable insights (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787125469 , 1787125467
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Data mining ; R (Computer program language) ; Social media ; Business ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Tap into the realm of social media and unleash the power of analytics for data-driven insights using R About This Book A practical guide written to help leverage the power of the R eco-system to extract, process, analyze, visualize and model social media data Learn about data access, retrieval, cleaning, and curation methods for data originating from various social media platforms. Visualize and analyze data from social media platforms to understand and model complex relationships using various concepts and techniques such as Sentiment Analysis, Topic Modeling, Text Summarization, Recommendation Systems, Social Network Analysis, Classification, and Clustering. Who This Book Is For It is targeted at IT professionals, Data Scientists, Analysts, Developers, Machine Learning Enthusiasts, social media marketers and anyone with a keen interest in data, analytics, and generating insights from social data. Some background experience in R would be helpful, but not necessary, since this book is written keeping in mind, that readers can have varying levels of expertise. What You Will Learn Learn how to tap into data from diverse social media platforms using the R ecosystem Use social media data to formulate and solve real-world problems Analyze user social networks and communities using concepts from graph theory and network analysis Learn to detect opinion and sentiment, extract themes, topics, and trends from unstructured noisy text data from diverse social media channels Understand the art of representing actionable insights with effective visualizations Analyze data from major social media channels such as Twitter, Facebook, Flickr, Foursquare, Github, StackExchange, and so on Learn to leverage popular R packages such as ggplot2, topicmodels, caret, e1071, tm, wordcloud, twittR, Rfacebook, dplyr, reshape2, and many more In Detail The Internet has truly become humongous, especially with the rise of various forms of social media in the last decade, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the reader to understand the current social media landscape and to learn how analytics can be leveraged to derive insights from it. This data can be analyzed to gain valuable insights into the behavior and engagement of users, organizations, businesses, and brands. It will help readers frame business problems and solve them using social data. The book will also cover several practical r...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed June 16, 2017)
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    Android development with Kotlin : learn Android application development with the extensive features of Kotlin (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787128989 , 1787128989
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Java (Computer program language) ; Mobile apps ; Development ; Computer programming ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Learn how to make Android development much faster using a variety of Kotlin features, from basics to advanced, to write better quality code. About This Book Leverage specific features of Kotlin to ease Android application development Write code based on both object oriented and functional programming to build robust applications Filled with various practical examples so you can easily apply your knowledge to real world scenarios Identify the improved way of dealing with common Java patterns Who This Book Is For This book is for developers who have a basic understanding of Java language and have 6-12 months of experience with Android development and developers who feel comfortable with OOP concepts. What You Will Learn Run a Kotlin application and understand the integration with Android Studio Incorporate Kotlin into new/existing Android Java based project Learn about Kotlin type system to deal with null safety and immutability Define various types of classes and deal with properties Define collections and transform them in functional way Define extensions, new behaviours to existing libraries and Android framework classes Use generic type variance modifiers to define subtyping relationship between generic types Build a sample application In Detail Nowadays, improved application development does not just mean building better performing applications. It has become crucial to find improved ways of writing code. Kotlin is a language that helps developers build amazing Android applications easily and effectively. This book discusses Kotlin features in context of Android development. It demonstrates how common examples that are typical for Android development, can be simplified using Kotlin. It also shows all the benefits, improvements and new possibilities provided by this language. The book is divided in three modules that show the power of Kotlin and teach you how to use it properly. Each module present features in different levels of advancement. The first module covers Kotlin basics. This module will lay a firm foundation for the rest of the chapters so you are able to read and understand most of the Kotlin code. The next module dives deeper into the building blocks of Kotlin, such as functions, classes, and function types. You will learn how Kotlin brings many improvements to the table by improving common Java concepts and decreasing code verbosity. The last module presents features that are not present in Java. You will learn how certain task...
    Note: Description based on online resource; title from title page (Safari, viewed September 25, 2017)
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    Docker orchestration : a concise, fast-paced guide to orchestrating and deploying scalable services with Docker (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787129207 , 1787129209
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Open source software ; Application software ; Development ; Cloud computing ; Electronic books ; Electronic books ; local
    Abstract: A concise, fast-paced guide to orchestrating and deploying scalable services with Docker About This Book Explore the new features added to the core Docker Engine to make multi-container orchestration easy Leverage tools such as Docker Machine, Swarm, Compose, and third-party tools such as Kubernetes, Mesosphere, and CoreOS to orchestrate containers Use Docker Compose with Swarm and apply rolling updates for zero downtime deployments Who This Book Is For This book is aimed at Sysadmins and DevOps engineers who know what Docker does and are now looking to manage multiple containers on multiple hosts using the orchestration feature. What You Will Learn Build scalable, reliable services with Docker See how to manage a service in Docker using Docker Swarm, Kubernetes, and Mesosphere Discover simpler orchestration tools such as CoreOS/Fleet and Rancher Cattle Understand cluster-wide logging, system monitoring, and troubleshooting Build, test, and deploy containers using Continuous Integration Deploy cluster hosts on cloud services and automate your infrastructure In Detail Docker orchestration is what you need when transitioning from deploying containers individually on a single host to deploying complex multi-container apps on many machines. This book covers the new orchestration features of Docker 1.12 and helps you efficiently build, test, and deploy your application using Docker. You will be shown how to build multi-container applications using Docker Compose. You will also be introduced to the building blocks for multi-host Docker clusters such as registry, overlay networks, and shared storage using practical examples. This book gives an overview of core tools such as Docker Machine, Swarm, and Compose which will enhance your orchestration skills. You'll learn how to set up a swarm using the decentralized building block. Next, you'll be shown how to make the most out of the in-built orchestration feature of Docker engine and you'll use third-party tools such as Kubernetes, Mesosphere, and CoreOS to orchestrate your existing process. Finally, you will learn to deploy cluster hosts on cloud services and automate your infrastructure. Style and approach This comprehensive guide will take you through the orchestration feature of Docker. Using practical examples, you will discover various tools that can be used to manage multiple containers with ease.
    Note: Description based on online resource; title from cover (Safari, viewed February 9, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787122123/?ar
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    Python social media analytics : analyze and visualize data from Twitter, YouTube, GitHub, and more (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787126756 , 1787126757
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Data mining ; Social media ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more Analyze and extract actionable insights from your social data using various Python tools A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What You Will Learn Understand the basics of social media mining Use PyMongo to clean, store, and access data in MongoDB Understand user reactions and emotion detection on Facebook Perform Twitter sentiment analysis and entity recognition using Python Analyze video and campaign performance on YouTube Mine popular trends on GitHub and predict the next big technology Extract conversational topics on public internet forums Analyze user interests on Pinterest Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes. Style and approach This book follows a step-by-step approach to teach readers the concepts of social media analytics using th...
    Note: Description based on online resource; title from title page (Safari, viewed August 14, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787121485/?ar
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    Containers in OpenStack : leverage OpenStack services to make the most of Docker, Kubernetes and Mesos (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788391924 , 1788391926
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Cloud computing ; Information technology ; Management ; Application software ; Development ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: A practical book which will help the readers understand how the container ecosystem and OpenStack work together. About This Book Gets you acquainted with containerization in private cloud Learn to effectively manage and secure your containers in OpenStack Practical use cases on container deployment and management using OpenStack components Who This Book Is For This book is targeted towards cloud engineers, system administrators, or anyone from the production team who works on OpenStack cloud. This book act as an end to end guide for anyone who wants to start using the concept of containerization on private cloud. Some basic knowledge of Docker and Kubernetes will help. What You Will Learn Understand the role of containers in the OpenStack ecosystem Learn about containers and different types of container runtimes tools. Understand containerization in OpenStack with respect to the deployment framework, platform services, application deployment, and security Get skilled in using OpenStack to run your applications inside containers Explore the best practices of using containers in OpenStack. In Detail Containers are one of the most talked about technologies of recent times. They have become increasingly popular as they are changing the way we develop, deploy, and run software applications. OpenStack gets tremendous traction as it is used by many organizations across the globe and as containers gain in popularity and become complex, it's necessary for OpenStack to provide various infrastructure resources for containers, such as compute, network, and storage. Containers in OpenStack answers the question, how can OpenStack keep ahead of the increasing challenges of container technology? You will start by getting familiar with container and OpenStack basics, so that you understand how the container ecosystem and OpenStack work together. To understand networking, managing application services and deployment tools, the book has dedicated chapters for different OpenStack projects: Magnum, Zun, Kuryr, Murano, and Kolla. Towards the end, you will be introduced to some best practices to secure your containers and COE on OpenStack, with an overview of using each OpenStack projects for different use cases. Style and approach An end to end guide for anyone who wants to start using the concept of containerization on private cloud.
    Note: Description based on online resource; title from title page (Safari, viewed February 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788394383/?ar
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    Mastering MongoDB 3.x : an expert's guide to building fault-tolerant MongoDB applications (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781783982615 , 1783982616
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: MongoDB ; Open source software ; Object-oriented databases ; Database management ; Software ; Electronic books ; Electronic books ; local
    Abstract: An expert's guide to build fault tolerant MongoDB application About This Book Master the advanced modeling, querying, and administration techniques in MongoDB and become a MongoDB expert Covers the latest updates and Big Data features frequently used by professional MongoDB developers and administrators If your goal is to become a certified MongoDB professional, this book is your perfect companion Who This Book Is For Mastering MongoDB is a book for database developers, architects, and administrators who want to learn how to use MongoDB more effectively and productively. If you have experience in, and are interested in working with, NoSQL databases to build apps and websites, then this book is for you. What You Will Learn Get hands-on with advanced querying techniques such as indexing, expressions, arrays, and more. Configure, monitor, and maintain highly scalable MongoDB environment like an expert. Master replication and data sharding to optimize read/write performance. Design secure and robust applications based on MongoDB. Administer MongoDB-based applications on-premise or in the cloud Scale MongoDB to achieve your design goals Integrate MongoDB with big data sources to process huge amounts of data In Detail MongoDB has grown to become the de facto NoSQL database with millions of users - from small startups to Fortune 500 companies. Addressing the limitations of SQL schema-based databases, MongoDB pioneered a shift of focus for DevOps and offered sharding and replication maintainable by DevOps teams. The book is based on MongoDB 3.x and covers topics ranging from database querying using the shell, built in drivers, and popular ODM mappers to more advanced topics such as sharding, high availability, and integration with big data sources. You will get an overview of MongoDB and how to play to its strengths, with relevant use cases. After that, you will learn how to query MongoDB effectively and make use of indexes as much as possible. The next part deals with the administration of MongoDB installations on-premise or in the cloud. We deal with database internals in the next section, explaining storage systems and how they can affect performance. The last section of this book deals with replication and MongoDB scaling, along with integration with heterogeneous data sources. By the end this book, you will be equipped with all the required industry skills and knowledge to become a certified MongoDB developer and administrator. Style and approach...
    Note: Description based on online resource; title from title page (viewed January 2, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781783982608/?ar
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    Pandas cookbook : recipes for scientific computing, time series analysis and data visualization using Python (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781784393342 , 1784393347
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Management ; Data processing ; Machine learning ; Information visualization ; Data mining ; Electronic data processing ; Electronic books ; Electronic books ; local
    Abstract: Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysis About This Book Use the power of pandas to solve most complex scientific computing problems with ease Leverage fast, robust data structures in pandas to gain useful insights from your data Practical, easy to implement recipes for quick solutions to common problems in data using pandas Who This Book Is For This book is for data scientists, analysts and Python developers who wish to explore data analysis and scientific computing in a practical, hands-on manner. The recipes included in this book are suitable for both novice and advanced users, and contain helpful tips, tricks and caveats wherever necessary. Some understanding of pandas will be helpful, but not mandatory. What You Will Learn Master the fundamentals of pandas to quickly begin exploring any dataset Isolate any subset of data by properly selecting and querying the data Split data into independent groups before applying aggregations and transformations to each group Restructure data into tidy form to make data analysis and visualization easier Prepare real-world messy datasets for machine learning Combine and merge data from different sources through pandas SQL-like operations Utilize pandas unparalleled time series functionality Create beautiful and insightful visualizations through pandas direct hooks to Matplotlib and Seaborn In Detail This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter. Many advanced recipes combine several different features across the pandas library to generate results. Style and approach The author relies on his vast experience teaching pandas in a professional setting to deliver very detailed exp...
    Note: Description based on online resource; title from title page (Safari, viewed November 14, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781784393878/?ar
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    Mastering Java for data science : building data science applications in Java (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785887390 , 1785887394
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Java (Computer program language) ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrie...
    Note: Description based on online resource; title from title page (viewed May 15, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781782174271/?ar
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    Learning Elastic Stack 6.0 : a beginner's guide to distributed search, analytics, and visualization using Elasticsearch, Logstash, and Kibana (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787285866 , 1787285863
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Information visualization ; Electronic data processing Distributed processing ; Open source software
    Note: Description based on online resource; title from title page (Safari, viewed January 31, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781787281868/?ar
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    Learning Google BigQuery : a beginner's guide to mining massive datasets through interactive analysis (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787286290 , 1787286290
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Google BigQuery ; Google Analytics ; Data mining
    Note: Description based on online resource; title from title page (viewed January 31, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781787288591/?ar
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    Splunk : enterprise operational intelligence delivered : demystify big data and discover how to bring operational intelligence to your data to revolutionize your work (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787288256 , 1787288250
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Enterprise resource planning ; Management information systems ; Electronic data processing ; Data mining ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Demystify Big Data and discover how to bring operational intelligence to your data to revolutionize your work About This Book Get maximum use out of your data with Splunk's exceptional analysis and visualization capabilities Analyze and understand your operational data skillfully using this end-to-end course Full coverage of high-level Splunk techniques such as advanced searches, manipulations, and visualization Who This Book Is For This course is for software developers who wish to use Splunk for operational intelligence to make sense of their machine data. The content in this course will appeal to individuals from all facets of business, IT, security, product, marketing, and many more What You Will Learn Install and configure the latest version of Splunk. Use Splunk to gather, analyze, and report data Create Dashboards and Visualizations that make data meaningful Model and accelerate data and perform pivot-based reporting Integrate advanced JavaScript charts and leverage Splunk's APIs Develop and Manage apps in Splunk Integrate Splunk with R and Tableau using SDKs In Detail Splunk is an extremely powerful tool for searching, exploring, and visualizing data of all types. Splunk is becoming increasingly popular, as more and more businesses, both large and small, discover its ease and usefulness. Analysts, managers, students, and others can quickly learn how to use the data from their systems, networks, web traffic, and social media to make attractive and informative reports. This course will teach everything right from installing and configuring Splunk. The first module is for anyone who wants to manage data with Splunk. You'll start with very basics of Splunk - installing Splunk - before then moving on to searching machine data with Splunk. You will gather data from different sources, isolate them by indexes, classify them into source types, and tag them with the essential fields. With more than 70 recipes on hand in the second module that demonstrate all of Splunk's features, not only will you find quick solutions to common problems, but you'll also learn a wide range of strategies and uncover new ideas that will make you rethink what operational intelligence means to you and your organization. Dive deep into Splunk to find the most efficient solution to your data problems in the third module. Create the robust Splunk solutions you need to make informed decisions in big data machine analytics. From visualizations to enterprise integration,...
    Note: "Learning path.". - Includes bibliographical references and index. - Description based on online resource; title from cover (viewed April 18, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787288256/?ar
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    NGINX cookbook : make the most of your web server (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786469779 , 1786469774
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Web servers ; Computer programs ; HTTP (Computer network protocol) ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: A practical book on real-world NGINX deployments to get you up and running quickly. About This Book Be the first to immerse yourself in the NGINX 1.9x web server and explore the plethora of advanced features. Master the skills of load balancing TCP-based applications and implementing HTTP/2. A recipe-based approach book that provides you with up-to-date information on NGINX, allowing you to implement specific use cases immediately. Who This Book Is For This book is aimed at smaller-to-medium developers, who are just getting started with NGINX. It assumes they already understand the basics of how a web server works and how basic networking works. What You Will Learn Practical, real-world examples and recipes on how to use NGINX Common CMS deployments such as WordPress, Joomla and more NGINX configurations for frameworks such as Ruby on Rails, Django and more Detailed SSL recipes, including HTTP/2 Real world rewrite examples Basic web and TCP load balancing configuration Bandwidth management and connection limiting Detailed NGINX deployment scenarios with Docker Performance tuning and monitoring of your NGINX deployments OpenResty deployment guides Advanced deployments with NGINX Plus features In Detail NGINX Cookbook covers the basics of configuring NGINX as a web server for use with common web frameworks such as WordPress and Ruby on Rails, through to utilization as a reverse proxy. Designed as a go-to reference guide, this book will give you practical answers based on real-world deployments to get you up and running quickly. Recipes have also been provided for multiple SSL configurations, different logging scenarios, practical rewrites, and multiple load balancing scenarios. Advanced topics include covering bandwidth management, Docker container usage, performance tuning, OpenResty, and the NGINX Plus commercial features. By the time you've read this book, you will be able to adapt and use a wide variety of NGINX implementations to solve any problems you have.
    Note: Description based on online resource; title from title page (Safari, viewed September 26, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781786466174/?ar
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    IBM SPSS Modeler essentials : effective techniques for building powerful data mining and predictive analytics solutions (2017)
    Birmingham, UK : Packt Publishing
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: SPSS (Computer file) ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Get to grips with the fundamentals of data mining and predictive analytics with IBM SPSS Modeler About This Book Get up?and-running with IBM SPSS Modeler without going into too much depth. Identify interesting relationships within your data and build effective data mining and predictive analytics solutions A quick, easy?to-follow guide to give you a fundamental understanding of SPSS Modeler, written by the best in the business Who This Book Is For This book is ideal for those who are new to SPSS Modeler and want to start using it as quickly as possible, without going into too much detail. An understanding of basic data mining concepts will be helpful, to get the best out of the book. What You Will Learn Understand the basics of data mining and familiarize yourself with Modeler's visual programming interface Import data into Modeler and learn how to properly declare metadata Obtain summary statistics and audit the quality of your data Prepare data for modeling by selecting and sorting cases, identifying and removing duplicates, combining data files, and modifying and creating fields Assess simple relationships using various statistical and graphing techniques Get an overview of the different types of models available in Modeler Build a decision tree model and assess its results Score new data and export predictions In Detail IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler's easy to learn ?visual programming? style. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. This bo...
    Note: Description based on online resource; title from title page (viewed February 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788291118/?ar
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    Mastering Elastic Stack : get the most out of the Elastic Stack for various complex analytics using this comprehensive and practical guide (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786468055 , 1786468050
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Client/server computing ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Get the most out of the Elastic Stack for various complex analytics using this comprehensive and practical guide About This Book Your one-stop solution to perform advanced analytics with Elasticsearch, Logstash, and Kibana Learn how to make better sense of your data by searching, analyzing, and logging data in a systematic way This highly practical guide takes you through an advanced implementation on the ELK stack in your enterprise environment Who This Book Is For This book cater to developers using the Elastic stack in their day-to-day work who are familiar with the basics of Elasticsearch, Logstash, and Kibana, and now want to become an expert at using the Elastic stack for data analytics. What You Will Learn Build a pipeline with help of Logstash and Beats to visualize Elasticsearch data in Kibana Use Beats to ship any type of data to the Elastic stack Understand Elasticsearch APIs, modules, and other advanced concepts Explore Logstash and it's plugins Discover how to utilize the new Kibana UI for advanced analytics See how to work with the Elastic Stack using other advanced configurations Customize the Elastic Stack and plugin development for each of the component Work with the Elastic Stack in a production environment Explore the various components of X-Pack in detail. In Detail Even structured data is useless if it can't help you to take strategic decisions and improve existing system. If you love to play with data, or your job requires you to process custom log formats, design a scalable analysis system, and manage logs to do real-time data analysis, this book is your one-stop solution. By combining the massively popular Elasticsearch, Logstash, Beats, and Kibana, elastic.co has advanced the end-to-end stack that delivers actionable insights in real time from almost any type of structured or unstructured data source. If your job requires you to process custom log formats, design a scalable analysis system, explore a variety of data, and manage logs, this book is your one-stop solution. You will learn how to create real-time dashboards and how to manage the life cycle of logs in detail through real-life scenarios. This book brushes up your basic knowledge on implementing the Elastic Stack and then dives deeper into complex and advanced implementations of the Elastic Stack. We'll help you to solve data analytics challenges using the Elastic Stack and provide practical steps on centralized logging and real-time analytics with the Elastic...
    Note: Description based on online resource; title from cover (Safari, viewed April 27, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781786460011/?ar
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    NHibernate 4.x cookbook : over 90 incredible and powerful recipes to help you efficiently use NHibernate in your application (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781784394110 , 1784394114
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Hibernate (Electronic resource) ; Object-oriented programming (Computer science) ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Over 90 incredible and powerful recipes to help you efficiently use NHibernate in your application About This Book Master the full range of NHibernate features through detailed example recipes that you can quickly apply to your own applications Reduce hours of application development time and get a better application architecture and improved performance Create, maintain, and update your database structure automatically with the help of NHibernate Who This Book Is For This book is written for .NET developers who want to use NHibernate and those who want to deepen their knowledge of the platform. Examples are written in C# and XML. Some basic knowledge of SQL is assumed. If you build .NET applications that use relational databases, this book is for you. What You Will Learn Create a persistent object model to move data in and out of your database Build the database from your model automatically Configure NHibernate for use with WebForms, MVC, WPF, and WinForms applications Create database queries using a variety of methods Improve the performance of your applications using a variety of techniques Build an infrastructure for fast, easy, test-driven development of your data access layer Implement entity validation, auditing, full-text search, horizontal partitioning (sharding), and spatial queries using NHibernate Contrib projects In Detail NHibernate is a mature, flexible, scalable, and feature-complete open source project for data access. Although it sounds like an easy task to build and maintain database applications, it can be challenging to get beyond the basics and develop applications that meet your needs perfectly. NHibernate allows you to use plain SQL and stored procedures less and keep focus on your application logic instead. Learning the best practices for a NHibernate-based application will help you avoid problems and ensure that your project is a success. The book will take you from the absolute basics of NHibernate through to its most advanced features, showing you how to take full advantage of each concept to quickly create amazing database applications. You will learn several techniques for each of the four core NHibernate tasks - configuration, mapping, session and transaction management, and querying - and which techniques fit best with various types of applications. In short, you will be able to build an application using NHibernate by the end of the book. You will also learn how to best implement enterprise application archite...
    Note: Includes index. - Description based on online resource; title from cover (viewed February 16, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781784396428/?ar
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    Deployment with Docker : apply continuous integration models, deploy applications quicker, and scale at large by putting Docker to work (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786463227 , 1786463229
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Open source software ; Application software Development ; Cloud computing
    Note: Description based on online resource; title from title page (Safari, viewed January 3, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781786469007/?ar
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    Learning Apache Apex : Real-time streaming applications with Apex (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788294119 , 1788294114
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Apache Apex ; Data mining ; Big data
    Note: Description based on online resource; title from title page (viewed January 9, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788296403/?ar
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    Stream Analytics with Microsoft Azure : real-time data processing for quick insights using Azure Stream Analytics (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788390620 , 1788390628
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Microsoft Azure (Computing platform) ; Cloud computing ; Data mining
    Note: Description based on online resource; title from title page (viewed January 10, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788395908/?ar
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    Getting started with Kubernetes : harness the power of Kubernetes to manage Docker deployments with ease (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787284135 , 1787284131
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Linux ; Application software ; Development ; Virtual computer systems ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Learn how to schedule and run application containers using Kubernetes. About This Book Get well-versed with the fundamentals of Kubernetes and get it production-ready for deployments Confidently manage your container clusters and networks using Kubernetes This practical guide will show you container application examples throughout to illustrate the concepts and features of Kubernetes Who This Book Is For This book is for developers, sys admins, and DevOps engineers who want to automate the deployment process and scale their applications. You do not need any knowledge about Kubernetes. What You Will Learn Download, install, and configure the Kubernetes codebase Understand the core concepts of a Kubernetes cluster Be able to set up and access monitoring and logging for Kubernetes clusters Set up external access to applications running in the cluster Understand how CoreOS and Kubernetes can help you achieve greater performance and container implementation agility Run multiple clusters and manage from a single control plane Explore container security as well as securing Kubernetes clusters Work with third-party extensions and tools In Detail Kubernetes has continued to grow and achieve broad adoption across various industries, helping you to orchestrate and automate container deployments on a massive scale. This book will give you a complete understanding of Kubernetes and how to get a cluster up and running. You will develop an understanding of the installation and configuration process. The book will then focus on the core Kubernetes constructs such as pods, services, replica sets, replication controllers, and labels. You will also understand how cluster level networking is done in Kubernetes. The book will also show you how to manage deployments and perform updates with minimal downtime. Additionally, you will learn about operational aspects of Kubernetes such as monitoring and logging. Advanced concepts such as container security and cluster federation will also be covered. Finally, you will learn about the wider Kubernetes ecosystem with OCP, CoreOS, and Tectonic and explore the third-party extensions and tools that can be used with Kubernetes. By the end of the book, you will have a complete understanding of the Kubernetes platform and will start deploying applications on it. Style and approach This straightforward guide will help you understand how to move your container applications into production through best practices and a step-by-step...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed June 30, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787283367/?ar
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    Learning Kibana 5.0 : exploit the visualization capabilities of Kibana and build powerful interactive dashboards (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786465795 , 1786465795
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Information visualization ; Dashboards (Management information systems) ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Exploit the visualization capabilities of Kibana and build powerful interactive dashboards About This Book Introduction to data-driven architecture and the Elastic stack Build effective dashboards for data visualization and explore datasets with Elastic Graph A comprehensive guide to learning scalable data visualization techniques in Kibana Who This Book Is For If you are a developer, data visualization engineer, or data scientist who wants to get the best of data visualization at scale then this book is perfect for you. A basic understanding of Elasticsearch and Logstash is required to make the best use of this book. What You Will Learn How to create visualizations in Kibana Ingest log data, structure an Elasticsearch cluster, and create visualization assets in Kibana Embed Kibana visualization on web pages Scaffold, develop, and deploy new Kibana & Timelion customizations Build a metrics dashboard in Timelion based on time series data Use the Graph plugin visualization feature and leverage a graph query Create, implement, package, and deploy a new custom plugin Use Prelert to solve anomaly detection challenges In Detail Kibana is an open source data visualization platform that allows you to interact with your data through stunning, powerful graphics. Its simple, browser-based interface enables you to quickly create and share dynamic dashboards that display changes to Elasticsearch queries in real time. In this book, you'll learn how to use the Elastic stack on top of a data architecture to visualize data in real time. All data architectures have different requirements and expectations when it comes to visualizing the data, whether it's logging analytics, metrics, business analytics, graph analytics, or scaling them as per your business requirements. This book will help you master Elastic visualization tools and adapt them to the requirements of your project. You will start by learning how to use the basic visualization features of Kibana 5. Then you will be shown how to implement a pure metric analytics architecture and visualize it using Timelion, a very recent and trendy feature of the Elastic stack. You will learn how to correlate data using the brand-new Graph visualization and build relationships between documents. Finally, you will be familiarized with the setup of a Kibana development environment so that you can build a custom Kibana plugin. By the end of this book you will have all the information needed to take your Elastic stack sk...
    Note: Description based on online resource; title from cover (Safari, viewed March 9, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781786463005/?ar
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    Mastering Kubernetes : automating container deployment and management (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786469854 , 1786469855
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Linux ; Application software ; Development ; Virtual computer systems ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Master the art of container management utilizing the power of Kubernetes. About This Book This practical guide demystifies Kubernetes and ensures that your clusters are always available, scalable, and up to date Discover new features such as autoscaling, rolling updates, resource quotas, and cluster size Master the skills of designing and deploying large clusters on various cloud platforms Who This Book Is For The book is for system administrators and developers who have intermediate level of knowledge with Kubernetes and are now waiting to master its advanced features. You should also have basic networking knowledge. This advanced-level book provides a pathway to master Kubernetes. What You Will Learn Architect a robust Kubernetes cluster for long-time operation Discover the advantages of running Kubernetes on GCE, AWS, Azure, and bare metal See the identity model of Kubernetes and options for cluster federation Monitor and troubleshoot Kubernetes clusters and run a highly available Kubernetes Create and configure custom Kubernetes resources and use third-party resources in your automation workflows Discover the art of running complex stateful applications in your container environment Deliver applications as standard packages In Detail Kubernetes is an open source system to automate the deployment, scaling, and management of containerized applications. If you are running more than just a few containers or want automated management of your containers, you need Kubernetes. This book mainly focuses on the advanced management of Kubernetes clusters. It covers problems that arise when you start using container orchestration in production. We start by giving you an overview of the guiding principles in Kubernetes design and show you the best practises in the fields of security, high availability, and cluster federation. You will discover how to run complex stateful microservices on Kubernetes including advanced features as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage back ends. Using real-world use cases, we explain the options for network configuration and provides guidelines on how to set up, operate, and troubleshoot various Kubernetes networking plugins. Finally, we cover custom resource development and utilization in automation and maintenance workflows. By the end of this book, you'll know everything you need to know to go from intermediate to advanced level. Style and approach Delving into the design ...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed June 15, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781786461001/?ar
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    Enterprise application architecture with .NET Core : an architectural journey into Microsoft .NET open source platform (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786469373 , 1786469375
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Open source software ; Microsoft .NET Core (software framework) ; Application software ; Performance ; Application software ; Testing ; Electronic books ; Electronic books ; local
    Abstract: Architect and design highly scalable, robust, clean and highly performant applications in .NET Core About This Book Incorporate architectural soft-skills such as DevOps and Agile methodologies to enhance program-level objectives Gain knowledge of architectural approaches on the likes of SOA architecture and microservices to provide traceability and rationale for architectural decisions Explore a variety of practical use cases and code examples to implement the tools and techniques described in the book Who This Book Is For This book is for experienced .NET developers who are aspiring to become architects of enterprise-grade applications, as well as software architects who would like to leverage .NET to create effective blueprints of applications. What You Will Learn Grasp the important aspects and best practices of application lifecycle management Leverage the popular ALM tools, application insights, and their usage to monitor performance, testability, and optimization tools in an enterprise Explore various authentication models such as social media-based authentication, 2FA and OpenID Connect, learn authorization techniques Explore Azure with various solution approaches for Microservices and Serverless architecture along with Docker containers Gain knowledge about the recent market trends and practices and how they can be achieved with .NET Core and Microsoft tools and technologies In Detail If you want to design and develop enterprise applications using .NET Core as the development framework and learn about industry-wide best practices and guidelines, then this book is for you. The book starts with a brief introduction to enterprise architecture, which will help you to understand what enterprise architecture is and what the key components are. It will then teach you about the types of patterns and the principles of software development, and explain the various aspects of distributed computing to keep your applications effective and scalable. These chapters act as a catalyst to start the practical implementation, and design and develop applications using different architectural approaches, such as layered architecture, service oriented architecture, microservices and cloud-specific solutions. Gradually, you will learn about the different approaches and models of the Security framework and explore various authentication models and authorization techniques, such as social media-based authentication and safe storage using app secrets. By the end...
    Note: Description based on online resource; title from title page (viewed May 16, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781786468888/?ar
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    OpenStack for architects : design and implement successful private clouds with OpenStack (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781784396442 , 1784396443
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: OpenStack (Electronic resource) ; Cloud computing ; Computing platforms ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Design and implement successful private clouds with OpenStack About This Book Explore the various design choices available for cloud architects within an OpenStack deployment Craft an OpenStack architecture and deployment pipeline to meet the unique needs of your organization Create a product roadmap for Infrastructure as a Service in your organization using this hands-on guide Who This Book Is For This book is written especially for those who will design OpenStack clouds and lead their implementation. These people are typically cloud architects, but may also be in product management, systems engineering, or enterprise architecture. What You Will Learn Familiarize yourself with the components of OpenStack Build an increasingly complex OpenStack lab deployment Write compelling documentation for the architecture teams within your organization Apply Agile configuration management techniques to deploy OpenStack Integrate OpenStack with your organization's identity management, provisioning, and billing systems Configure a robust virtual environment for users to interact with Use enterprise security guidelines for your OpenStack deployment Create a product roadmap that delivers functionality quickly to the users of your platform In Detail Over the last five years, hundreds of organizations have successfully implemented Infrastructure as a Service (IaaS) platforms based on OpenStack. The huge amount of investment from these organizations, industry giants such as IBM and HP, as well as open source leaders such as Red Hat have led analysts to label OpenStack as the most important open source technology since the Linux operating system. Because of its ambitious scope, OpenStack is a complex and fast-evolving open source project that requires a diverse skill-set to design and implement it. This guide leads you through each of the major decision points that you'll face while architecting an OpenStack private cloud for your organization. At each point, we offer you advice based on the experience we've gained from designing and leading successful OpenStack projects in a wide range of industries. Each chapter also includes lab material that gives you a chance to install and configure the technologies used to build production-quality OpenStack clouds. Most importantly, we focus on ensuring that your OpenStack project meets the needs of your organization, which will guarantee a successful rollout. Style and approach This is practical, hands-on guide to impleme...
    Note: Includes bibliographical references. - Description based on online resource; title from cover (Safari, viewed March 1, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781784395100/?ar
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    HBase high performance cookbook : exciting projects that will teach you how complex data can be exploited to gain maximum insights (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781783983070 , 1783983078
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Distributed databases ; Handbooks, manuals, etc ; Electronic data processing ; Distributed processing ; Database management ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Exciting projects that will teach you how complex data can be exploited to gain maximum insights About This Book Architect a good HBase cluster for a very large distributed system Get to grips with the concepts of performance tuning with HBase A practical guide full of engaging recipes and attractive screenshots to enhance your system's performance Who This Book Is For This book is intended for developers and architects who want to know all about HBase at a hands-on level. This book is also for big data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic scalable database solution in the big data space. What You Will Learn Configure HBase from a high performance perspective Grab data from various RDBMS/Flat files into the HBASE systems Understand table design and perform CRUD operations Find out how the communication between the client and server happens in HBase Grasp when to use and avoid MapReduce and how to perform various tasks with it Get to know the concepts of scaling with HBase through practical examples Set up Hbase in the Cloud for a small scale environment Integrate HBase with other tools including ElasticSearch In Detail Apache HBase is a non-relational NoSQL database management system that runs on top of HDFS. It is an open source, disturbed, versioned, column-oriented store and is written in Java to provide random real-time access to big Data. We'll start off by ensuring you have a solid understanding the basics of HBase, followed by giving you a thorough explanation of architecting a HBase cluster as per our project specifications. Next, we will explore the scalable structure of tables and we will be able to communicate with the HBase client. After this, we'll show you the intricacies of MapReduce and the art of performance tuning with HBase. Following this, we'll explain the concepts pertaining to scaling with HBase. Finally, you will get an understanding of how to integrate HBase with other tools such as ElasticSearch. By the end of this book, you will have learned enough to exploit HBase for boost system performance. Style and approach This book is intended for software quality assurance/testing professionals, software project managers, or software developers with prior experience in using Selenium and Java to test web-based applications. This books also provides examples for C#, Python, and Ruby users.
    Note: Includes index. - Description based on online resource; title from cover (viewed February 16, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781783983063/?ar
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    Frank Kane's Taming big data with Apache Spark and Python : real-world examples to help you analyze large datasets with Apache Spark (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787288300 , 1787288307
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: SPARK (Electronic resource) ; Data mining ; Python (Computer program language) ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available in a book. Understand and analyze large data sets using Spark on a single system or on a cluster. About This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. If you have some programming experience in Python, and want to learn how to process large amounts of data using Apache Spark, Frank Kane's Taming Big Data with Apache Spark and Python will also help you. What You Will Learn Find out how you can identify Big Data problems as Spark problems Install and run Apache Spark on your computer or on a cluster Analyze large data sets across many CPUs using Spark's Resilient Distributed Datasets Implement machine learning on Spark using the MLlib library Process continuous streams of data in real time using the Spark streaming module Perform complex network analysis using Spark's GraphX library Use Amazon's Elastic MapReduce service to run your Spark jobs on a cluster In Detail Frank Kane's Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you'll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain ? quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease. Style and approach Frank Kane's Taming Big Data with Apache Spark and Python is a hands-on tutorial with over 15 real-world examples carefully explained by Frank in a step-by-step manner. The examples vary i...
    Note: Description based on online resource; title from title page (Safari, viewed July 24, 2017)
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    Mastering Apache Spark 2.x : scalable analytics faster than ever (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785285226 , 178528522X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Data mining ; Information retrieval ; Electronic books ; Electronic books ; local
    Abstract: Advanced analytics on your Big Data with latest Apache Spark 2.x About This Book An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities. Extend your data processing capabilities to process huge chunk of data in minimum time using advanced concepts in Spark. Master the art of real-time processing with the help of Apache Spark 2.x Who This Book Is For If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected. What You Will Learn Examine Advanced Machine Learning and DeepLearning with MLlib, SparkML, SystemML, H2O and DeepLearning4J Study highly optimised unified batch and real-time data processing using SparkSQL and Structured Streaming Evaluate large-scale Graph Processing and Analysis using GraphX and GraphFrames Apply Apache Spark in Elastic deployments using Jupyter and Zeppelin Notebooks, Docker, Kubernetes and the IBM Cloud Understand internal details of cost based optimizers used in Catalyst, SystemML and GraphFrames Learn how specific parameter settings affect overall performance of an Apache Spark cluster Leverage Scala, R and python for your data science projects In Detail Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and SQL. This book aims to take your knowledge of Spark to the next level by teaching you how to expand Spark's functionality and implement your data flows and machine/deep learning programs on top of the platform. The book commences with an overview of the Spark ecosystem. It will introduce you to Project Tungsten and Catalyst, two of the major advancements of Apache Spark 2.x. You will understand how memory management and binary processing, cache-aware computation, and code generation are used to speed things up dramatically. The book extends to show how to incorporate H20, SystemML, and Deeplearning4j for machine learning, and Jupyter Notebooks and Kubernetes/Docker for cloud-based Spark. During the course of the book, you will learn about the latest enhancements to Apache Spark 2.x, such as interactive querying of live data and unifying DataFrames and Datasets. You will also learn about the updates on the APIs ...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed August 14, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781786462749/?ar
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    Implementing Qlik Sense : design, develop, and validate BI solutions for consultants (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786466600 , 1786466600
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Management information systems ; Business intelligence ; Computer programs ; Information visualization ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Become a full-fledged Qlik Sense Consultant with the help of this unique guide About This Book Become a successful Qlik consultant with the help of this insightful guide Build what is in line as well as exceeding your customer's expectations from your Qlik Sense solutions using this highly practical guide Build result-driven optimized BI solutions using Qlik with the help of industry examples Who This Book Is For If you have basic familiarity with Qlik Sense and want to upgrade your skills to become a full-fledged Qlik Consultant, this book is for you. With this book, you will be able to create efficient business intelligence solutions that would fetch client satisfaction, and in turn, more projects. What You Will Learn Understand the importance and expectations of a consultant's role Engage with the customer to understand the ir goals and future objectives Design the optimum architecture, using the best practices for the development and implementation of your projects Ensure successful adoption using real-life examples to make your learning complete Learn about the important stages of a Qlik project's life cycle In Detail Qlik Sense is a leading platform for business intelligence (BI) solutions. Qlik Sense helps organizations in making informed decisions based on the data they have. This book will teach you how to effectively use Qlik for optimum customer satisfaction. You will undergo a metamorphosis from a developer to a consultant who is capable of building the most suitable BI solutions for your clients. The book will take you through several business cases ? this will give you enough insight to understand the needs of the client clearly and build a BI solution that meets or exceeds their expectations. Starting from the pre-project activities, you will go to the actual execution of the project, the implementation, and even maintenance. This book will give you all the information you need - from the strategy to requirement gathering to implementing BI solutions using Qlik Sense. The book will empower you to take the right decisions in tricky and diffi cult situations while developing analytics and dashboards. Style and approach This book will be a hands-on guide that will teach you all the what-to-do's, when-to-do's, and how-to-do's for becoming a successful Qlik Sense Consultant. With the help of various business scenarios, the book will cover real-world problems that you can relate to. Various solutions in the book will be backed up by t...
    Note: Description based on online resource; title from title page (Safari, viewed November 10, 2017)
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    Mastering Spark for data science : master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785888281 , 1785888285
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Data mining ; Machine learning ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products About This Book Develop and apply advanced analytical techniques with Spark Learn how to tell a compelling story with data science using Spark's ecosystem Explore data at scale and work with cutting edge data science methods Who This Book Is For This book is for those who have beginner-level familiarity with the Spark architecture and data science applications, especially those who are looking for a challenge and want to learn cutting edge techniques. This book assumes working knowledge of data science, common machine learning methods, and popular data science tools, and assumes you have previously run proof of concept studies and built prototypes. What You Will Learn Learn the design patterns that integrate Spark into industrialized data science pipelines See how commercial data scientists design scalable code and reusable code for data science services Explore cutting edge data science methods so that you can study trends and causality Discover advanced programming techniques using RDD and the DataFrame and Dataset APIs Find out how Spark can be used as a universal ingestion engine tool and as a web scraper Practice the implementation of advanced topics in graph processing, such as community detection and contact chaining Get to know the best practices when performing Extended Exploratory Data Analysis, commonly used in commercial data science teams Study advanced Spark concepts, solution design patterns, and integration architectures Demonstrate powerful data science pipelines In Detail Data science seeks to transform the world using data, and this is typically achieved through disrupting and changing real processes in real industries. In order to operate at this level you need to build data science solutions of substance ?solutions that solve real problems. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs. This book deep dives into using Spark to deliver production-grade data science solutions. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLli...
    Note: Description based on online resource; title from cover (Safari, viewed April 19, 2017)
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    Scala and Spark for big data analytics : tame big data with Scala and Apache Spark! (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781783550500 , 1783550503
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Data mining ; Scala (Computer program language) ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye! About This Book Learn Scala's sophisticated type system that combines Functional Programming and object-oriented concepts Work on a wide array of applications, from simple batch jobs to stream processing and machine learning Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark Who This Book Is For Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. What You Will Learn Understand object-oriented & functional programming concepts of Scala In-depth understanding of Scala collection APIs Work with RDD and DataFrame to learn Spark's core abstractions Analysing structured and unstructured data using SparkSQL and GraphX Scalable and fault-tolerant streaming application development using Spark structured streaming Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML Build clustering models to cluster a vast amount of data Understand tuning, debugging, and monitoring Spark applications Deploy Spark applications on real clusters in Standalone, Mesos, and YARN In Detail Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics u...
    Note: Description based on online resource; title from title page (Safari, viewed August 9, 2017)
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    Troubleshooting Docker : strategically design, troubleshoot, and automate Docker containers from development to deployment (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785285363 , 178528536X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Linux ; Application software ; Development ; Computer software ; Development ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Strategically design, troubleshoot, and automate Docker containers from development to deployment About This Book Utilize current and emergent technologies for effective Docker orchestration and management A step-by-step guide to diagnosing and fixing problems with Docker containers. Who This Book Is For This book is intended for seasoned solutions architects, developers, and programmers, system engineers, and administrators to help you troubleshoot common areas of Docker containerization. If you are looking to build production-ready Docker containers for automated deployment, you will be able to master and troubleshoot both the basic functions and the advanced features of Docker. Advanced familiarity with the Linux command line syntax, unit testing, the Docker Registry, Github, and leading container hosting platforms and Cloud Service Providers (CSP) are the prerequisites. What You Will Learn Install Docker ecosystem tools and services, Microservices and N-tier applications Create re-usable, portable containers with help of automation tools Network and inter-link containers Attach volumes securely to containers Consume and troubleshoot Docker APIs Troubleshooting issue of Docker deployment in Public cloud Ease the process of container management with Kubernetes In Detail This book will traverse some common best practices to for complex application scenarios where troubleshooting can be successfully employed to provide the repeatable processes and advantages that containers can deliver. This book will be a practical guide showing how to fix real-life issues related to installation, memory, Dockerfile syntax, connection, authorization, networking and so on in Docker. This book will also teach how to solve errors that occur during advanced setup and administration and deployment in a step-by-step fashion. By sequentially working through the real-world production scenarios in each chapter throughout the book, you will gain insight into and mastery of common areas not only for effective troubleshooting, but ways and means to avoid troubleshooting in the first place. This book will also cover tips and tricks that make the workflow easier. Style and approach An easy-to-follow guide full of interactive examples of real-world development and deployment scenarios. Ample screenshots, workflows, complementary tools, and related terminal commands are provided to address a wide range of practical and situational applications. Downloading the example code f...
    Note: Description based on online resource; title from cover (Safari, viewed April 19, 2017)
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    Learning Elasticsearch : distributed real-time search and analytics with Elasticsearch 5.x (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787129917 , 1787129918
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Lucene (Electronic resource) ; Web search engines ; Data mining ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Store, search, and analyze your data with ease using Elasticsearch 5.x About This Book Get to grips with the basics of Elasticsearch concepts and its APIs, and use them to create efficient applications Create large-scale Elasticsearch clusters and perform analytics using aggregation This comprehensive guide will get you up and running with Elasticsearch 5.x in no time Who This Book Is For If you want to build efficient search and analytics applications using Elasticsearch, this book is for you. It will also benefit developers who have worked with Lucene or Solr before and now want to work with Elasticsearch. No previous knowledge of Elasticsearch is expected. What You Will Learn See how to set up and configure Elasticsearch and Kibana Know how to ingest structured and unstructured data using Elasticsearch Understand how a search engine works and the concepts of relevance and scoring Find out how to query Elasticsearch with a high degree of performance and scalability Improve the user experience by using autocomplete, geolocation queries, and much more See how to slice and dice your data using Elasticsearch aggregations. Grasp how to use Kibana to explore and visualize your data Know how to host on Elastic Cloud and how to use the latest X-Pack features such as Graph and Alerting In Detail Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. You can use Elasticsearch for small or large applications with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently. You will install and set up Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data. Further on, you will learn to handle document relationships, work with geospatial data, and much more, with this easy-to-follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments. Style and approach This comprehensive guide will get you started with Elasticsearch 5.x, so you build a solid understanding of the basics. Every topic is explained in depth and ...
    Note: Description based on online resource; title from title page (Safari, viewed August 7, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787128453/?ar
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  • 96
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    Learning Pentaho data integration 8 CE : an end-to-end guide to exploring, transforming, and integrating your data across multiple sources (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788290074 , 1788290070
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Data integration (Computer science) ; Data mining ; Decision support systems ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guide About This Book Manipulate your data by exploring, transforming, validating, and integrating it using Pentaho Data Integration 8 CE A comprehensive guide exploring the features of Pentaho Data Integration 8 CE Connect to any database engine, explore the databases, and perform all kind of operations on relational databases Who This Book Is For This book is a must-have for software developers, business intelligence analysts, IT students, or anyone involved or interested in developing ETL solutions. If you plan on using Pentaho Data Integration for doing any data manipulation task, this book will help you as well. This book is also a good starting point for data warehouse designers, architects, or anyone who is responsible for data warehouse projects and needs to load data into them. What You Will Learn Explore the features and capabilities of Pentaho Data Integration 8 Community Edition Install and get started with PDI Learn the ins and outs of Spoon, the graphical designer tool Learn to get data from all kind of data sources, such as plain files, Excel spreadsheets, databases, and XML files Use Pentaho Data Integration to perform CRUD (create, read, update, and delete) operations on relationaldatabases Populate a data mart with Pentaho Data Integration Use Pentaho Data Integration to organize files and folders, run daily processes, deal with errors, and more In Detail Pentaho Data Integration(PDI) is an intuitive and graphical environment packed with drag-and-drop design and powerful Extract-Tranform-Load (ETL) capabilities. This book shows and explains the new interactive features of Spoon, the revamped look and feel, and the newest features of the tool including transformations and jobs Executors and the invaluable Metadata Injection capability. We begin with the installation of PDI software and then move on to cover all the key PDI concepts. Each of the chapter introduces new features, enabling you to gradually get practicing with the tool. First, you will learn to do all kind of data manipulation and work with simple plain files. Then, the book teaches you how you can work with relational databases inside PDI. Moreover, you will be given a primer on data warehouse concepts and you will learn how to load data in a data warehouse. During the course of this book, you will be familiarized with its intuitive, graphical and drag-and-drop design envir...
    Note: Description based on online resource; title from title page (Safari, viewed January 12, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788292436/?ar
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  • 97
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    Qlik sense : advanced data visualization for your organization : learning path : create smart data visualizations and predictive analytics solutions (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788998727 , 1788998723
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Management information systems ; Business intelligence ; Computer programs ; Information visualization ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Perform Interactive Data Analysis with Smarter Visualizations and Support your Enterprise-wide Analytical Needs About This Book Get a practical demonstration of discovering data for sales, human resources, and more using Qlik Sense Create dynamic dashboards for business intelligence and predictive analytics Create and collaborate comprehensive analytical solutions using Rattle and Qlik Sense Who This Book Is For This course is for anyone who wishes to understand and utilize the various new approaches to business intelligence actively in their business practice. Knowing the basics of business intelligence concepts would be helpful when picking up this course, but is not mandatory. What You Will Learn Build simple visualization models with Rattle and Qlik Sense Desktop Get to grips with the life cycle and new visualization functions of a Qlik Sense application Discover simple ways to examine data and get it ready for analysis Visualize your data with Qlik Sense's engaging and informative graphs Build efficient and responsive Associative Models Optimize Qlik Sense for sales, human resources, and demographic data discovery Explore various tips and tricks of navigation for the Qlik Sense® front end Develop creative extensions for your Qlik Sense® dashboard In Detail Qlik Sense is powerful and creative visual analytics software that allows users to discover data, explore it, and dig out meaningful insights in order to make a profit and make decisions for your business. This course begins by introducing you to the features and functions of the most modern edition of Qlik Sense so you get to grips with the application. The course will teach you how to administer the data architecture in Qlik Sense, enabling you to customize your own Qlik Sense application for your business intelligence needs. It also contains numerous recipes to help you overcome challenging situations while creating fully featured desktop applications in Qlik Sense. It explains how to combine Rattle and Qlik Sense Desktop to apply predictive analytics to your data to develop real-world interactive data applications. The course includes premium content from three of our most popular books: Learning Qlik Sense: The Official Guide Second Edition Qlik Sense Cookbook Predictive Analytics using Rattle and Qlik Sense On completion of this course, you will be self-sufficient in improving your data analysis and will know how to apply predictive analytics to your datasets. Through this course,...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed January 26, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788994927/?ar
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  • 98
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    Big data analytics with Java : big data analytics - massive, predictive, social and self-driving (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787282193 , 1787282198
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Java (Computer program language) ; Data mining ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Learn the basics of analytics on big data using Java, machine learning and other big data tools About This Book Acquire real-world set of tools for building enterprise level data science applications Surpasses the barrier of other languages in data science and learn create useful object-oriented codes Extensive use of Java compliant big data tools like apache spark, Hadoop, etc. Who This Book Is For This book is for Java developers who are looking to perform data analysis in production environment. Those who wish to implement data analysis in their Big data applications will find this book helpful. What You Will Learn Start from simple analytic tasks on big data Get into more complex tasks with predictive analytics on big data using machine learning Learn real time analytic tasks Understand the concepts with examples and case studies Prepare and refine data for analysis Create charts in order to understand the data See various real-world datasets In Detail This book covers case studies such as sentiment analysis on a tweet dataset, recommendations on a movielens dataset, customer segmentation on an ecommerce dataset, and graph analysis on actual flights dataset. This book is an end-to-end guide to implement analytics on big data with Java. Java is the de facto language for major big data environments, including Hadoop. This book will teach you how to perform analytics on big data with production-friendly Java. This book basically divided into two sections. The first part is an introduction that will help the readers get acquainted with big data environments, whereas the second part will contain a hardcore discussion on all the concepts in analytics on big data. It will take you from data analysis and data visualization to the core concepts and advantages of machine learning, real-life usage of regression and classification using Naïve Bayes, a deep discussion on the concepts of clustering,and a review of simple neural networks on big data using deepLearning4j or plain Java Spark code. This book is a must-have book for Java developers who want to start learning big data analytics and want to use it in the real world. Style and approach The approach of book is to deliver practical learning modules in manageable content. Each chapter is a self-contained unit of a concept in big data analytics. Book will step by step builds the competency in the area of big data analytics. Examples using real world case studies to give ideas of real applications a...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed August 18, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787288980/?ar
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  • 99
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    R : predictive analysis : master the art of predictive modeling (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788290852 , 1788290852
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: R (Computer program language) ; Quantitative research ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Master the art of predictive modeling About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Familiarize yourself with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, Naïve Bayes, decision trees, text mining and so on. We emphasize important concepts, such as the bias-variance trade-off and over-fitting, which are pervasive in predictive modeling Who This Book Is For If you work with data and want to become an expert in predictive analysis and modeling, then this Learning Path will serve you well. It is intended for budding and seasoned practitioners of predictive modeling alike. You should have basic knowledge of the use of R, although it's not necessary to put this Learning Path to great use. What You Will Learn Get to know the basics of R's syntax and major data structures Write functions, load data, and install packages Use different data sources in R and know how to interface with databases, and request and load JSON and XML Identify the challenges and apply your knowledge about data analysis in R to imperfect real-world data Predict the future with reasonably simple algorithms Understand key data visualization and predictive analytic skills using R Understand the language of models and the predictive modeling process In Detail Predictive analytics is a field that uses data to build models that predict a future outcome of interest. It can be applied to a range of business strategies and has been a key player in search advertising and recommendation engines. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. This Learning Path will provide you with all the steps you need to master the art of predictive modeling with R. We start with an introduction to data analysis with R, and then gradually you'll get your feet wet with predictive modeling. You will get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. You will be able to solve the difficulties relating to performing data analysis in practice and find solutions to working with ?messy data?, large data, communicating results, and facilitating reproducibility. You will then perform key predictive...
    Note: "Learning path.". - Includes bibliographical references and index. - Description based on online resource; title from cover (viewed April 18, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781788290371/?ar
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  • 100
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    Implementing domain-specific languages with Xtext and Xtend : learn how to implement a DSL with Xtext and Xtend using easy-to-understand examples and best practices (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786463272 , 178646327X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Edition: Second edition.
    Series Statement: Community experience distilled
    Keywords: Programming languages (Electronic computers) ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Learn how to implement a DSL with Xtext and Xtend using easy-to-understand examples and best practices About This Book Leverage the latest features of Xtext and Xtend to develop a domain-specific language. Integrate Xtext with popular third party IDEs and get the best out of both worlds. Discover how to test a DSL implementation and how to customize runtime and IDE aspects of the DSL Who This Book Is For This book is targeted at programmers and developers who want to create a domain-specific language with Xtext. They should have a basic familiarity with Eclipse and its functionality. Previous experience with compiler implementation can be helpful but is not necessary since this book will explain all the development stages of a DSL. What You Will Learn Write Xtext grammar for a DSL; Use Xtend as an alternative to Java to write cleaner, easier-to-read, and more maintainable code; Build your Xtext DSLs easily with Maven/Tycho and Gradle; Write a code generator and an interpreter for a DSL; Explore the Xtext scoping mechanism for symbol resolution; Test most aspects of the DSL implementation with JUnit; Understand best practices in DSL implementations with Xtext and Xtend; Develop your Xtext DSLs using Continuous Integration mechanisms; Use an Xtext editor in a web application In Detail Xtext is an open source Eclipse framework for implementing domain-specific languages together with IDE functionalities. It lets you implement languages really quickly; most of all, it covers all aspects of a complete language infrastructure, including the parser, code generator, interpreter, and more. This book will enable you to implement Domain Specific Languages (DSL) efficiently, together with their IDE tooling, with Xtext and Xtend. Opening with brief coverage of Xtext features involved in DSL implementation, including integration in an IDE, the book will then introduce you to Xtend as this language will be used in all the examples throughout the book. You will then explore the typical programming development workflow with Xtext when we modify the grammar of the DSL. Further, the Xtend programming language (a fully-featured Java-like language tightly integrated with Java) will be introduced. We then explain the main concepts of Xtext, such as validation, code generation, and customizations of runtime and UI aspects. You will have learned how to test a DSL implemented in Xtext with JUnit and will progress to advanced concepts such as type checking and scoping. ...
    Note: Includes bibliographical references and index. - Description based on online resource; title from cover (viewed September 21, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781786464965/?ar
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