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  • English  (67)
  • Birmingham, UK : Packt Publishing  (67)
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  • English  (67)
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  • 1
    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
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
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  • 2
    Online Resource
    Online Resource
    Data science for marketing analytics (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789952100 , 1789952107
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Marketing ; Data processing ; Marketing research ; Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key Features Study new techniques for marketing analytics Explore uses of machine learning to power your marketing analyses Work through each stage of data analytics with the help of multiple examples and exercises Book Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learn Analyze and visualize data in Python using pandas and Matplotlib Study clustering techniques, such as hierarchical and k-means clustering Create customer segments based on manipulated data Predict customer lifetime value using linear regression Use classification algorithms to understand customer choice Optimize classification algorithms to extract maximal information Who this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.
    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/-/9781789959413/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
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  • 3
    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
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
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  • 4
    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
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    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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  • 6
    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
    Library Location Call Number Volume/Issue/Year Availability
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  • 7
    Online Resource
    Online Resource
    Hands-on deep learning with Apache Spark : build and deploy distributed deep learning applications on Apache Spark (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788999700 , 1788999703
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Machine learning ; Electronic data processing ; Distributed processing ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Speed up the design and implementation of deep learning solutions using Apache Spark Key Features Explore the world of distributed deep learning with Apache Spark Train neural networks with deep learning libraries such as BigDL and TensorFlow Develop Spark deep learning applications to intelligently handle large and complex datasets Book Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learn Understand the basics of deep learning Set up Apache Spark for deep learning Understand the principles of distribution modeling and different types of neural networks Obtain an understanding of deep learning algorithms Discover textual analysis and deep learning with Spark Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras Explore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.
    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/-/9781788994613/?ar
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  • 8
    Online Resource
    Online Resource
    Learning Tableau 2019 : tools for business intelligence, data prep, and visual analytics (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788838740 , 1788838742
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Tableau (Computer file) ; Information visualization ; Business intelligence ; Computer programs ; Electronic books ; Electronic books ; local
    Abstract: Create powerful data visualizations and unlock intelligent business insights with Tableau Key Features Explore all the latest Tableau 2019 features and redefine business analytics for your organization Create impressive data visualizations and interactive dashboards to get insights from your data Learn effective data storytelling to transform how your business leverages data and makes decisions Book Description Tableau is the gold standard of business intelligence and visual analytics tools in every industry. It enables rapid data visualization and interpretation with charts, graphs, dashboards, and much more. Updated with the latest features of Tableau, this book takes you from the foundations of the Tableau 2019 paradigm through to advanced topics. This third edition of the bestselling guide by Tableau Zen Master, Joshua Milligan, will help you come to grips with updated features, such as set actions and transparent views. Beginning with installation, you'll create your first visualizations with Tableau and then explore practical examples and advanced techniques. You'll create bar charts, tree maps, scatterplots, time series, and a variety of other visualizations. Next, you'll discover techniques to overcome challenges presented by data structure and quality and engage in effective data storytelling and decision making with business critical information. Finally, you'll be introduced to Tableau Prep, and learn how to use it to integrate and shape data for analysis. By the end of this book, you will be equipped to leverage the powerful features of Tableau 2019 for decision making. What you will learn Develop stunning visualizations that explain complexity with clarity Explore the exciting new features of Tableau Desktop and Tableau Prep Connect to various data sources to bring all your data together Uncover techniques to prep and structure your data for easy analysis Create and use calculations to solve problems and enrich analytics Master advanced topics such as sets, LOD calcs, and much more Enable smart decisions with clustering, distribution, and forecasting Share your data stories to build a culture of trust and action Who this book is for This Tableau book is for anyone who wants to understand data. If you're new to Tableau, don't worry. This book builds on the foundations to help you understand how Tableau really works and then builds on that knowledge with practical examples before moving on to advanced techniques. Working experience...
    Note: Previous edition published: 2016. - Description based on online resource; title from title page (Safari, viewed May 1, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788839525/?ar
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  • 9
    Online Resource
    Online Resource
    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
    Library Location Call Number Volume/Issue/Year Availability
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  • 10
    Online Resource
    Online Resource
    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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  • 11
    Online Resource
    Online Resource
    Big data analytics with Hadoop 3 : build highly effective analytics solutions to gain valuable insight into your big data (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788624954 , 1788624955
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Apache Hadoop ; Spark (Electronic resource : Apache Software Foundation) ; Big data ; Information visualization ; Application program interfaces (Computer software) ; Electronic books ; Electronic books ; local
    Abstract: Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 About This Book Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Who This Book Is For Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3's powerful features, or you're new to big data analytics. A basic understanding of the Java programming language is required. What You Will Learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce In Detail Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3's latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. Style and approach Filled with practical examples and use cases, this book will not only help you get up and running with Hadoop, bu...
    Note: Description based on online resource; title from title page (Safari, viewed June 27, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788628846/?ar
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  • 12
    Online Resource
    Online Resource
    IPython interactive computing and visualization cookbook : over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785881930 , 1785881930
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Command languages (Computer science) ; Information visualization ; Interactive computer systems ; Electronic books ; Electronic books ; local
    Abstract: Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. About This Book Leverage the Jupyter Notebook for interactive data science and visualization Become an expert in high-performance computing and visualization for data analysis and scientific modeling A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Who This Book Is For This book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods. What You Will Learn Master all features of the Jupyter Notebook Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments Visualize data and create interactive plots in the Jupyter Notebook Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn) Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV Simulate deterministic and stochastic dynamical systems in Python Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory In Detail Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed February 22, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781785888632/?ar
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  • 13
    Online Resource
    Online Resource
    Hands-on data science with Anaconda : utilize the right mix of tools to create high-performance data science applications (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788834735 , 1788834739
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    RVK:
    ST 250
    Keywords: ANACONDA (Electronic resource) ; Machine learning ; Information visualization ; Electronic data processing
    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/-/9781788831192/?ar
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  • 14
    Online Resource
    Online Resource
    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)
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  • 15
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    Applied data science with Python and Jupyter (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789951929 , 1789951925
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Information visualization ; Electronic data processing ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications. Key Features Get up and running with the Jupyter ecosystem and some example datasets Learn about key machine learning concepts such as SVM, KNN classifiers, and Random Forests Discover how you can use web scraping to gather and parse your own bespoke datasets Book Description Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations. What you will learn Get up and running with the Jupyter ecosystem Identify potential areas of investigation and perform exploratory data analysis Plan a machine learning classification strategy and train classification models Use validation curves and dimensionality reduction to tune and enhance your models Scrape tabular data from web pages and transform it into Pandas DataFrames Create interactive, web-friendly visualizations to clearly communicate your findings Who this book is for Applied Data Science with Python and Jupyter is ideal for professionals with a variety of job descriptions across a large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries such as Pandas, Matplotlib, and Pandas providing you a useful head start.
    Note: Description based on online resource; title from copyright page (Safari, viewed June 12, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789958171/?ar
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  • 16
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    Hands-on data visualization with Bokeh : interactive web plotting for Python using Bokeh (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789131314 , 1789131316
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Learn how to create interactive and visually aesthetic plots using the Bokeh package in Python About This Book A step by step approach to creating interactive plots with Bokeh Go from nstallation all the way to deploying your very own Bokeh application Work with a real time datasets to practice and create your very own plots and applications Who This Book Is For This book is well suited for data scientists and data analysts who want to perform interactive data visualization on their web browsers using Bokeh. Some exposure to Python programming will be helpful, but prior experience with Bokeh is not required. What You Will Learn Installing Bokeh and understanding its key concepts Creating plots using glyphs, the fundamental building blocks of Bokeh Creating plots using different data structures like NumPy and Pandas Using layouts and widgets to visually enhance your plots and add a layer of interactivity Building and hosting applications on the Bokeh server Creating advanced plots using spatial data In Detail Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free. This book gets you up to speed with Bokeh - a popular Python library for interactive data visualization. The book starts out by helping you understand how Bokeh works internally and how you can set up and install the package in your local machine. You then use a real world data set which uses stock data from Kaggle to create interactive and visually stunning plots. You will also learn how to leverage Bokeh using some advanced concepts such as plotting with spatial and geo data. Finally you will use all the concepts that you have learned in the previous chapters to create your very own Bokeh application from scratch. By the end of the book you will be able to create your very own Bokeh application. You will have gone through a step by step process that starts with understanding what Bokeh actually is and ends with building your very own Bokeh application filled with interactive and visually aesthetic plots. Style and approach This books take you through a step by step process that starts with understanding what Bokeh actually is and ends with building your very own Bokeh application filled with in...
    Note: Description based on online resource; title from title page (Safari, viewed August 28, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789135404/?ar
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  • 17
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    Qlik Sense cookbook : over 80 recipes on data analytics to solve business intelligence challenges (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788997171 , 1788997174
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Management information systems ; Business intelligence ; Computer programs ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Create dynamic dashboards to perform interactive analytics for business intelligence operations Key Features Explore newly added features in Qlik Sense Discover best practices to work with data using Qlik Sense Learn to implement advanced functions for better data insight Book Description Qlik Sense allows you to explore simple and complex data to reveal hidden insight and data relationships that help you make quality decisions for overall productivity. An expert Qlik Sense user can use its features for business intelligence in an enterprise environment effectively. Qlik Sense Cookbook is an excellent guide for all aspiring Qlik Sense developers and will empower you to create featured desktop applications to obtain daily insights at work. This book takes you through the basics and advanced functions of Qlik Sense February 2018 release. You'll start with a quick refresher on obtaining data from data files and databases, and move on to some more refined features including visualization, and scripting, as well as managing apps and user interfaces. You will then understand how to work with advanced functions like set analysis and set expressions. As you make your way through this book, you will uncover newly added features in Qlik Sense such as new visualizations, label expressions and colors for dimension and measures. By the end of this book, you will have explored various visualization extensions to create your own interactive dashboard with the required tips and tricks. This will help you overcome challenging situations while developing your applications in Qlik Sense. What you will learn Source, preview, and distribute your data through interactive dashboards Explore and work with the latest visualization functions Learn how to write and use script subroutines Make your UI advanced and intuitive with custom objects and indicators Use visualization extensions for your Qlik Sense dashboard Work with Aggr and learn to use it within set analysis Who this book is for Qlik Sense Cookbook is for data and BI analysts who want to become well versed with Qlik Sense to apply business intelligence in data. If you are a beginner in data analytics and want to adopt an independent recipe-based approach to learn the required concepts and services in detail, this book is ideal! Individuals with prior knowledge of its sister product, QlikView, will also benefit from this book. Familiarity with the basics of business intelligence is a prerequisite.
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed October 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788997058/?ar
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  • 18
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    Modern big data processing with Hadoop : expert techniques for architecting end-to-end big data solutions to get valuable insights (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787128811 , 1787128814
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Apache Hadoop ; Spark (Electronic resource : Apache Software Foundation) ; Big data ; Information visualization ; Application program interfaces (Computer software) ; Electronic books ; Electronic books ; local
    Abstract: A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop About This Book Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Who This Book Is For This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book. What You Will Learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari Design effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficiently In Detail The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowled...
    Note: Description based on online resource; title from title page (Safari, viewed May 2, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781787122765/?ar
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  • 19
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    Matplotlib for Python developers : effective techniques for data visualization with Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788628136 , 1788628136
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Matplotlib to visualize and understand your data more effectively About This Book Perform effective data visualization with Matplotlib and get actionable insights from your data Design attractive graphs, charts, and 2D plots, and deploy them to the web Get the most out of Matplotlib in this practical guide with updated code and examples Who This Book Is For This book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If you're a data scientist or analyst and wish to create attractive visualizations using Python, you'll find this book useful. Some knowledge of Python programming is all you need to get started. What You Will Learn Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of Matplotlib Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn Create interactive plots with real-time updates Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Django Write data visualization code that is readily expandable on the cloud platform In Detail Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you'll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You'll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you'll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you'll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to bu...
    Note: Previous edition published: 2009. - Description based on online resource; title from title page (Safari, viewed May 22, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788625173/?ar
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  • 20
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    Getting started with Haskell data analysis : put your data analysis techniques to work and generate publication-ready visualizations (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789808605 , 178980860X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Haskell (Computer program language) ; Information visualization ; Statistics ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Put your Haskell skills to work and generate publication-ready visualizations in no time at all Key Features Take your data analysis skills to the next level using the power of Haskell Understand regression analysis, perform multivariate regression, and untangle different cluster varieties Create publication-ready visualizations of data Book Description Every business and organization that collects data is capable of tapping into its own data to gain insights how to improve. Haskell is a purely functional and lazy programming language, well-suited to handling large data analysis problems. This book will take you through the more difficult problems of data analysis in a hands-on manner. This book will help you get up-to-speed with the basics of data analysis and approaches in the Haskell language. You'll learn about statistical computing, file formats (CSV and SQLite3), descriptive statistics, charts, and progress to more advanced concepts such as understanding the importance of normal distribution. While mathematics is a big part of data analysis, we've tried to keep this course simple and approachable so that you can apply what you learn to the real world. By the end of this book, you will have a thorough understanding of data analysis, and the different ways of analyzing data. You will have a mastery of all the tools and techniques in Haskell for effective data analysis. What you will learn Learn to parse a CSV file and read data into the Haskell environment Create Haskell functions for common descriptive statistics functions Create an SQLite3 database using an existing CSV file Learn the versatility of SELECT queries for slicing data into smaller chunks Apply regular expressions in large-scale datasets using both CSV and SQLite3 files Create a Kernel Density Estimator visualization using normal distribution Who this book is for This book is intended for people who wish to expand their knowledge of statistics and data analysis via real-world examples. A basic understanding of the Haskell language is expected. If you are feeling brave, you can jump right into the functional programming style.
    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/-/9781789802863/?ar
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  • 21
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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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  • 22
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    Generative adversarial networks cookbook : over 100 recipes to build generative models using Python, TensorFlow, and Keras (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789139587 , 1789139589
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Machine learning ; Python (Computer program language) ; Artificial intelligence ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key Features Understand the common architecture of different types of GANs Train, optimize, and deploy GAN applications using TensorFlow and Keras Build generative models with real-world data sets, including 2D and 3D data Book Description Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand. This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use. By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away. What you will learn Structure a GAN architecture in pseudocode Understand the common architecture for each of the GAN models you will build Implement different GAN architectures in TensorFlow and Keras Use different datasets to enable neural network functionality in GAN models Combine different GAN models and learn how to fine-tune them Produce a model that can take 2D images and produce 3D models Develop a GAN to do style transfer with Pix2Pix Who this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.
    Note: Description based on online resource; title from title page (Safari, viewed February 25, 2019)
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  • 23
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    Hands-on computer vision with Julia : build complex applications with advanced Julia packages for image processing, neural networks, and artificial intelligence (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788999236 , 1788999231
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Julia (Computer program language) ; Information visualization ; Neural networks (Computer science) ; Application software ; Development ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Explore the various packages in Julia that support image processing and build neural networks for video processing and object tracking. About This Book Build a full-fledged image processing application using JuliaImages Perform basic to advanced image and video stream processing with Julia's APIs Understand and optimize various features of OpenCV with easy examples Who This Book Is For Hands-On Computer Vision with Julia is for Julia developers who are interested in learning how to perform image processing and want to explore the field of computer vision. Basic knowledge of Julia will help you understand the concepts more effectively. What You Will Learn Analyze image metadata and identify critical data using JuliaImages Apply filters and improve image quality and color schemes Extract 2D features for image comparison using JuliaFeatures Cluster and classify images with KNN/SVM machine learning algorithms Recognize text in an image using the Tesseract library Use OpenCV to recognize specific objects or faces in images and videos Build neural network and classify images with MXNet In Detail Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it's easy to use and lets you write easy-to-compile and efficient machine code. This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. You'll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you'll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned. By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease. Style and approach Readers will be taken through various packages that support image processing in Julia, ...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed August 8, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788998796/?ar
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  • 24
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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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  • 25
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    Python data science essentials : a practitioner's guide covering essential data science principles, tools, and techniques (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789531893 , 1789531896
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Python (Computer program language) ; Database management ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Gain useful insights from your data using popular data science tools Key Features A one-stop guide to Python libraries such as pandas and NumPy Comprehensive coverage of data science operations such as data cleaning and data manipulation Choose scalable learning algorithms for your data science tasks Book Description Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn. The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You'll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost. By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users What you will learn Set up your data science toolbox on Windows, Mac, and Linux Use the core machine learning methods offered by the scikit-learn library Manipulate, fix, and explore data to solve data science problems Learn advanced explorative and manipulative techniques to solve data operations Optimize your machine learning models for optimized performance Explore and cluster graphs, taking advantage of interconnections and links in your data Who this book is for If you're a data science entrant, data analyst, or data engineer, this book will help you get ready to tackle real-world data science problems without wasting any time. Basic knowledge of probability/statistics and Python coding experience will assist you in understanding the concepts 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 an...
    Note: Description based on online resource; title from title page (viewed November 5, 2018)
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  • 26
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    QlikView, advanced data visualization : discover deeper insights with QlikView by building your own rich analytical applications from scratch (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789954173 , 1789954177
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Management information systems ; Information visualization ; Application software ; Development ; Business intelligence ; Computer programs ; Electronic books ; Electronic books ; local
    Abstract: Build powerful data analytics applications with this business intelligence tool and overcome all your business challenges Key Features Master time-saving techniques and make your QlikView development more efficient Perform geographical analysis and sentiment analysis in your QlikView applications Explore advanced QlikView techniques, tips, and tricks to deliver complex business requirements Book Description QlikView is one of the most flexible and powerful business intelligence platforms around, and if you want to transform data into insights, it is one of the best options you have at hand. Use this Learning Path, to explore the many features of QlikView to realize the potential of your data and present it as impactful and engaging visualizations. Each chapter in this Learning Path starts with an understanding of a business requirement and its associated data model and then helps you create insightful analysis and data visualizations around it. You will look at problems that you might encounter while visualizing complex data insights using QlikView, and learn how to troubleshoot these and other not-so-common errors. This Learning Path contains real-world examples from a variety of business domains, such as sales, finance, marketing, and human resources. With all the knowledge that you gain from this Learning Path, you will have all the experience you need to implement your next QlikView project like a pro. This Learning Path includes content from the following Packt products: QlikView for Developers by Miguel Angel Garcia, Barry Harmsen Mastering QlikView by Stephen Redmond Mastering QlikView Data Visualization by Karl Pover What you will learn Deliver common business requirements using advanced techniques Load data from disparate sources to build associative data models Understand when to apply more advanced data visualization Utilize the built-in aggregation functions for complex calculations Build a data architecture that supports scalable QlikView deployments Troubleshoot common data visualization errors in QlikView Protect your QlikView applications and data Who this book is for This Learning Path is designed for developers who want to go beyond their technical knowledge of QlikView and understand how to create analysis and data visualizations that solve real business needs. To grasp the concepts explained in this Learning Path, you should have a basic understanding of the common QlikView functions and some hands-on experience with the tool.
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed February 22, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789955996/?ar
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    Tableau 10 complete reference : transform your business with rich data visualizations and interactive dashboards with Tableau 10 (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789950380 , 1789950384
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Tableau (Computer file) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Explore and understand data with the powerful data visualization techniques of Tableau, and then communicate insights in powerful ways Key Features Apply best practices in data visualization and chart types exploration Explore the latest version of Tableau Desktop with hands-on examples Understand the fundamentals of Tableau storytelling Book Description Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You'll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. Last but not least, you'll learn about the power of storytelling through the creation of interactive dashboards in Tableau. Through this Learning Path, you will gain confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. This Learning Path includes content from the following Packt products: Learning Tableau 10 - Second Edition by Joshua N. Milligan Getting Started with Tableau 2018.x by Tristan Guillevin What you will learn Build effective visualizations, dashboards, and story points Build basic to more advanced charts with step-by-step recipes Become familiar row-level, aggregate, and table calculations Dig deep into data with clustering and distribution models Prepare and transform data for analysis Leverage Tableau's mapping capabilities to visualize data Use data storytelling techniques to aid decision making strategy Who this book is for Tableau 10 Complete Reference is designed for anyone who wants to understand their data better and represent it in an effective manner. It is al...
    Note: Description based on online resource; title from title page (Safari, viewed February 20, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789957082/?ar
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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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    Mastering Matplotlib 2.x : effective data visualization techniques with Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789618174 , 1789618177
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Understand and build beautiful and advanced plots with Matplotlib and Python Key Features Practical guide with hands-on examples to design interactive plots Advanced techniques to constructing complex plots Explore 3D plotting and visualization using Jupyter Notebook Book Description In this book, you'll get hands-on with customizing your data plots with the help of Matplotlib. You'll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You'll explore non-trivial layouts, Pylab customization, and more about tile configuration. You'll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you'll explore them further in this book. You'll delve into niche plots and visualize ordinal and tabular data. In this book, you'll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you'll learn how to create interactive plots with the help of Jupyter. Learn expert techniques for effective data visualization using Matplotlib 3 and Python with our latest offering -- Matplotlib 3.0 Cookbook What you will learn Deal with non-trivial and unusual plots Understanding Basemap methods Customize and represent data in 3D Construct Non-Cartesian and vector plots Design interactive plots using Jupyter Notebook Make movies for enhanced data representation Who this book is for This book is aimed at individuals who want to explore data visualization techniques. A basic knowledge of Matplotlib and Python is required.
    Note: Description based on online resource; title from title page (Safari, viewed February 14, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789617696/?ar
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    Apache Spark deep learning cookbook : over 80 recipes that streamline deep learning in a distributed environment with Apache Spark (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788471558 , 1788471555
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Machine learning ; Electronic data processing ; Distributed processing ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: A solution-based guide to put your deep learning models into production with the power of Apache Spark Key Features Discover practical recipes for distributed deep learning with Apache Spark Learn to use libraries such as Keras and TensorFlow Solve problems in order to train your deep learning models on Apache Spark Book Description With deep learning gaining rapid mainstream adoption in modern-day industries, organizations are looking for ways to unite popular big data tools with highly efficient deep learning libraries. As a result, this will help deep learning models train with higher efficiency and speed. With the help of the Apache Spark Deep Learning Cookbook, you'll work through specific recipes to generate outcomes for deep learning algorithms, without getting bogged down in theory. From setting up Apache Spark for deep learning to implementing types of neural net, this book tackles both common and not so common problems to perform deep learning on a distributed environment. In addition to this, you'll get access to deep learning code within Spark that can be reused to answer similar problems or tweaked to answer slightly different problems. You will also learn how to stream and cluster your data with Spark. Once you have got to grips with the basics, you'll explore how to implement and deploy deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in Spark, using popular libraries such as TensorFlow and Keras. By the end of the book, you'll have the expertise to train and deploy efficient deep learning models on Apache Spark. What you will learn Set up a fully functional Spark environment Understand practical machine learning and deep learning concepts Apply built-in machine learning libraries within Spark Explore libraries that are compatible with TensorFlow and Keras Explore NLP models such as Word2vec and TF-IDF on Spark Organize dataframes for deep learning evaluation Apply testing and training modeling to ensure accuracy Access readily available code that may be reusable Who this book is for If you're looking for a practical and highly useful resource for implementing efficiently distributed deep learning models with Apache Spark, then the Apache Spark Deep Learning Cookbook is for you. Knowledge of the core machine learning concepts and a basic understanding of the Apache Spark framework is required to get the best out of this book. Additionally, some programming knowledge in Python ...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed August 15, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788474221/?ar
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    Big data visualization : learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 1785284169 , 9781785284168
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Big data ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization About This Book This unique guide teaches you how to visualize your cluttered, huge amounts of big data with ease It is rich with ample options and solid use cases for big data visualization, and is a must-have book for your shelf Improve your decision-making by visualizing your big data the right way Who This Book Is For This book is for data analysts or those with a basic knowledge of big data analysis who want to learn big data visualization in order to make their analysis more useful. You need sufficient knowledge of big data platform tools such as Hadoop and also some experience with programming languages such as R. This book will be great for those who are familiar with conventional data visualizations and now want to widen their horizon by exploring big data visualizations. What You Will Learn Understand how basic analytics is affected by big data Deep dive into effective and efficient ways of visualizing big data Get to know various approaches (using various technologies) to address the challenges of visualizing big data Comprehend the concepts and models used to visualize big data Know how to visualize big data in real time and for different use cases Understand how to integrate popular dashboard visualization tools such as Splunk and Tableau Get to know the value and process of integrating visual big data with BI tools such as Tableau Make sense of the visualization options for big data, based upon the best suited visualization techniques for big data In Detail When it comes to big data, regular data visualization tools with basic features become insufficient. This book covers the concepts and models used to visualize big data, with a focus on efficient visualizations. This book works around big data visualizations and the challenges around visualizing big data and address characteristic challenges of visualizing like speed in accessing, understanding/adding context to, improving the quality of the data, displaying results, outliers, and so on. We focus on the most popular libraries to execute the tasks of big data visualization and explore "big data oriented" tools such as Hadoop and Tableau. We will show you how data changes with different variables and for different use cases with step-through topics such as: importing data to something like Hadoop, basic analytics. The choice of visualizations depends ...
    Note: Description based on online resource; title from cover (viewed April 17, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781785281945/?ar
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    Learning SAP Analytics Cloud : discover, plan, predict, collaborate, visualize, and extend all in one solution (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788291842 , 1788291840
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: SAP Analytics Cloud ; Cloud computing ; Business ; Data processing ; Information visualization ; Management information systems ; Electronic books ; Electronic books ; local
    Abstract: Start making better business decisions backed by data About This Book Predict new opportunities and risks in a few mouse clicks Eliminate complexity with tools that let you plan, analyze, and collaborate in context - in real time Discover, visualize, plan, and predict in a single product with agile BI tools Who This Book Is For This book targets IT professionals, business analysts, BI developers, managers, newcomers to SAP Analytics Cloud, and ultimately anyone who wants to learn from self-paced, professional guidance and needs a solid foundation in SAP Analytics Cloud. What You Will Learn A clear understanding of SAP Analytics Cloud platform Create data models using different data sources, including Excel and text files . Present professional analyses using different types of charts, tables, geo maps, and more Using stories, drill up and down instantly to analyze data from various angles Share completed stories with other team members or compile them in SAP Digital Boardroom agendas for presentation to major stakeholders Export the results of a story to a PDF file Save time by planning, analyzing, predicting, and collaborating in context Discover, visualize, plan, and predict in one product as opposed to separate solutions In Detail The book starts with the basics of SAP Analytics Cloud (formerly known as SAP BusinessObjects Cloud) and exposes almost every significant feature a beginner needs to master. Packed with illustrations and short, essential, to-the-point descriptions, the book provides a unique learning experience. Your journey of exploration starts with a basic introduction to the SAP Analytics Cloud platform. You will then learn about different segments of the product, such as Models, Stories, Digital Boardroom, and so on. Then, you are introduced to the product's interface: the Home screen, the main menu, and more. Then comes the hands-on aspect of the book, which starts with model creation. Next, you learn how to utilize a model to prepare different types of stories(reports) with the help of charts, tables, Geo Maps, and more. In the final chapters of this book, you will learn about Digital Boardroom, Collaboration, and Administration. Style and approach The easy-to-follow visual instructions provided in this book help business users and report developers create simple and complex stories (reports) quickly
    Note: Description based on online resource; title from title page (Safari, viewed July 27, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781788290883/?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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    R data visualization recipes : a cookbook with 65+ data visualization recipes for smarter decision-making (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788394079 , 1788394070
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: R (Computer program language) ; Information visualization ; Decision making Mathematical models
    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/-/9781788398312/?ar
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    Learning D3.js 4 mapping : build cutting-edge maps and visualizations with JavaScript (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787284258 , 1787284255
    Language: English
    Pages: 1 online resource (1 volume) , illustrations, maps
    Edition: Second edition
    Parallel Title: Erscheint auch als
    Keywords: JavaScript (Computer program language) ; Information visualization ; Digital mapping
    Note: Description based on online resource; title from title page (Safari, viewed January 12, 2018). - Previous edition published: 2014
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781787280175/?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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    Matplotlib 2.x by example : multi-dimensional charts, graphs, and plots (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788292139 , 1788292138
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Unlock deeper insights into visualization in form of 2D and 3D graphs using Matplotlib 2.x About This Book Create and customize live graphs, by adding style, color, font to make appealing graphs. A complete guide with insightful use cases and examples to perform data visualizations with Matplotlib's extensive toolkits. Create timestamp data visualizations on 2D and 3D graphs in form of plots, histogram, bar charts, scatterplots and more. Who This Book Is For This book is for anyone interested in data visualization, to get insights from big data with Python and Matplotlib 2.x. With this book you will be able to extend your knowledge and learn how to use python code in order to visualize your data with Matplotlib. Basic knowledge of Python is expected. What You Will Learn Familiarize with the latest features in Matplotlib 2.x Create data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots and many more. Make clear and appealing figures for scientific publications. Create interactive charts and animation. Extend the functionalities of Matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn. Design intuitive infographics for effective storytelling. In Detail Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization. Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts. By the end of this book, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable. Style and approach Step by step comprehensive guide filled with real world examples.
    Note: Description based on online resource; title from title page (Safari, viewed September 25, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781788295260/?ar
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    Analytics for the Internet of Things (IoT) : intelligent analytics for your intelligent devices (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787127579 , 1787127575
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Internet of things ; Mobile computing ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Break through the hype and learn how to extract actionable intelligence from the flood of IoT data About This Book Make better business decisions and acquire greater control of your IoT infrastructure Learn techniques to solve unique problems associated with IoT and examine and analyze data from your IoT devices Uncover the business potential generated by data from IoT devices and bring down business costs Who This Book Is For This book targets developers, IoT professionals, and those in the field of data science who are trying to solve business problems through IoT devices and would like to analyze IoT data. IoT enthusiasts, managers, and entrepreneurs who would like to make the most of IoT will find this equally useful. A prior knowledge of IoT would be helpful but is not necessary. Some prior programming experience would be useful What You Will Learn Overcome the challenges IoT data brings to analytics Understand the variety of transmission protocols for IoT along with their strengths and weaknesses Learn how data flows from the IoT device to the final data set Develop techniques to wring value from IoT data Apply geospatial analytics to IoT data Use machine learning as a predictive method on IoT data Implement best strategies to get the most from IoT analytics Master the economics of IoT analytics in order to optimize business value In Detail We start with the perplexing task of extracting value from huge amounts of barely intelligible data. The data takes a convoluted route just to be on the servers for analysis, but insights can emerge through visualization and statistical modeling techniques. You will learn to extract value from IoT big data using multiple analytic techniques. Next we review how IoT devices generate data and how the information travels over networks. You'll get to know strategies to collect and store the data to optimize the potential for analytics, and strategies to handle data quality concerns. Cloud resources are a great match for IoT analytics, so Amazon Web Services, Microsoft Azure, and PTC ThingWorx are reviewed in detail next. Geospatial analytics is then introduced as a way to leverage location information. Combining IoT data with environmental data is also discussed as a way to enhance predictive capability. We'll also review the economics of IoT analytics and you'll discover ways to optimize business value. By the end of the book, you'll know how to handle scale for both data storage and analytics, how Apache...
    Note: Description based on online resource; title from title page (Safari, viewed August 10, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781787120730/?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)
    URL: https://learning.oreilly.com/library/view/-/9781786460448/?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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    Python : advanced predictive analytics : gain practical insights by exploiting data in your business to build advanced predictive modeling applications (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788993036 , 1788993039
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Python (Computer program language) ; Information visualization ; Application software Development
    Note: Description based on online resource; title from cover (Safari, viewed February 1, 2018). - "Learning path."
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788992367/?ar
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  • 42
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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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    Python : data analytics and visualization : understand, evaluate, visualize data (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788294850 , 1788294858
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Information visualization ; Quantitative research ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Understand, evaluate, and visualize data About This Book Learn basic steps of data analysis and how to use Python and its packages A step-by-step guide to predictive modeling including tips, tricks, and best practices Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. What You Will Learn Get acquainted with NumPy and use arrays and array-oriented computing in data analysis Process and analyze data using the time-series capabilities of Pandas Understand the statistical and mathematical concepts behind predictive analytics algorithms Data visualization with Matplotlib Interactive plotting with NumPy, Scipy, and MKL functions Build financial models using Monte-Carlo simulations Create directed graphs and multi-graphs Advanced visualization with D3 In Detail You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn. After this, you will move on to a data analytics specialization - predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling. After this, you will get all the practical guidance you need to help you on the journey...
    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/-/9781788290098/?ar
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    Python : end-to-end data analysis : leverage the power of Python to clean, scrape, analyze, and visualize your data : a course in three modules (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788396547 , 1788396545
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Information visualization ; Quantitative research ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Python to clean, scrape, analyze, and visualize your data About This Book Clean, format, and explore your data using the popular Python libraries and get valuable insights from it Analyze big data sets; create attractive visualizations; manipulate and process various data types using NumPy, SciPy, and matplotlib; and more Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For This course is for developers, analysts, and data scientists who want to learn data analysis from scratch. This course will provide you with a solid foundation from which to analyze data with varying complexity. A working knowledge of Python (and a strong interest in playing with your data) is recommended. What You Will Learn Understand the importance of data analysis and master its processing steps Get comfortable using Python and its associated data analysis libraries such as Pandas, NumPy, and SciPy Clean and transform your data and apply advanced statistical analysis to create attractive visualizations Analyze images and time series data Mine text and analyze social networks Perform web scraping and work with different databases, Hadoop, and Spark Use statistical models to discover patterns in data Detect similarities and differences in data with clustering Work with Jupyter Notebook to produce publication-ready figures to be included in reports In Detail Data analysis is the process of applying logical and analytical reasoning to study each component of data present in the system. Python is a multi-domain, high-level, programming language that offers a range of tools and libraries suitable for all purposes, it has slowly evolved as one of the primary languages for data science. Have you ever imagined becoming an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? If yes, look no further, this is the course you need! In this course, we will get you started with Python data analysis by introducing the basics of data analysis and supported Python libraries such as matplotlib, NumPy, and pandas. Create visualizations by choosing color maps, different shapes, sizes, and palettes then delve into statistical data analysis using distribution algorithms and correlations. You'll then find your way around different data and numerical problems, get to grips with Spark and HDFS, and set up migration s...
    Note: Authors: Phuong Vo. T.H. [and four others]. Cf. Credits page. - Includes bibliographical references and index. - Description based on online resource; title from title page (Safari, viewed June 26, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781788394697/?ar
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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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    Data visualization : representing information on modern web : unleash the power of data by creating interactive, engaging, and compelling visualizations for the web : a course in three modules (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787125070 , 1787125076
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Unleash the power of data by creating interactive, engaging, and compelling visualizations for the web About This Book Get a portable, versatile, and flexible data visualization design approach that will help you navigate the complex path towards success Get thorough explanation of the many visual variables and visualization taxonomy to provide you with a menu of creative options A comprehensive and contemporary introduction to data-driven visualization design and the most effective approaches to designing impact-maximizing and cognition-amplifying visualizations Who This Book Is For This course is for developers who are excited about data and who want to share that excitement with others and it will be handy for the web developers or data scientists who want to create interactive visualizations for the web. Prior knowledge of developing web applications is required. You should have a working knowledge of both JavaScript and HTML. What You Will Learn Harness the power of D3 by building interactive and real-time data-driven web visualizations Find out how to use JavaScript to create compelling visualizations of social data Identify the purpose of your visualization and your project's parameters to determine overriding design considerations across your project's execution Apply critical thinking to visualization design and get intimate with your dataset to identify its potential visual characteristics Explore the various features of HTML5 to design creative visualizations Discover what data is available on Stack Overflow, Facebook, Twitter, and Google+ Gain a solid understanding of the common D3 development idioms Find out how to write basic D3 code for server using Node.js In Detail Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories, and key insights that are locked away. This learning path is divided into three modules. The first module will equip you with the key techniques required to overcome contemporary data visualization challenges. After getting familiar with key concepts of data visualization, it's time to incorporate it with various technologies. In the second module, Social Data Visualization with HTML5 and JavaScript, it teaches you how to leverage HTML5 techniques through JavaScript to build visualizations. It also cle...
    Note: Authors: Andy Kirk, Simon Timms, AEndrew Rininsland, Swizec Teller. Cf. Credits page. - Includes bibliographical references and index. - Description based on online resource; title from title page (Safari, viewed November 2, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781787129764/?ar
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    Tableau : creating interactive data visualizations : illustrate your data in a more interactive way by implementing data visualization principles and creating visual stories using Tableau : a course in three modules (2016)
    Birmingham, UK : Packt Publishing
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Tableau (Computer file) ; Information visualization ; Visual analytics ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Illustrate your data in a more interactive way by implementing data visualization principles and creating visual stories using Tableau About This Book Use data visualization principles to help you to design dashboards that enlighten and support business decisions Integrate your data to provide mashed-up dashboards Connect to various data sources and understand what data is appropriate for Tableau Public Understand chart types and when to use specific chart types with different types of data Who This Book Is For Data scientists who have just started using Tableau and want to build on the skills using practical examples. Familiarity with previous versions of Tableau will be helpful, but not necessary. What You Will Learn Customize your designs to meet the needs of your business using Tableau Use Tableau to prototype, develop, and deploy the final dashboard Create filled maps and use any shape file Discover features of Tableau Public, from basic to advanced Build geographic maps to bring context to data Create filters and actions to allow greater interactivity to Tableau Public visualizations and dashboards Publish and embed Tableau visualizations and dashboards in articles In Detail With increasing interest for data visualization in the media, businesses are looking to create effective dashboards that engage as well as communicate the truth of data. Tableau makes data accessible to everyone, and is a great way of sharing enterprise dashboards across the business. Tableau is a revolutionary toolkit that lets you simply and effectively create high-quality data visualizations. This course starts with making you familiar with its features and enable you to develop and enhance your dashboard skills, starting with an overview of what dashboard is, followed by how you can collect data using various mathematical formulas. Next, you'll learn to filter and group data, as well as how to use various functions to present the data in an appealing and accurate way. In the first module, you will learn how to use the key advanced string functions to play with data and images. You will be walked through the various features of Tableau including dual axes, scatterplot matrices, heat maps, and sizing.In the second module, you'll start with getting your data into Tableau, move onto generating progressively complex graphics, and end with the finishing touches and packaging your work for distribution. This module is filled with practical examples to help you create fi...
    Note: Authors: Jen Stirrup, Ashutosh Nandeshwar, Ashley Ohmann, Matt Floyd. Cf. Credits page. - Includes bibliographical references and index. - Description based on online resource; title from title page (Safari, viewed October 6, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781787124196/?ar
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    Learning Tableau 10 : learn how to create effective data visualizations with Tableau and unlock a smarter approach to business analytics : it might just transform your organization (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786468925 , 1786468921
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Tableau (Computer file) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Learn how to create effective data visualizations with Tableau and unlock a smarter approach to business analytics. It might just transform your organization About This Book Create stylish visualizations and dashboards that explain complexity with clarity Learn effective data storytelling to transform how your business uses ideas and makes decisions Explore all the new features in Tableau 10 and start to redefine what business analytics means to your organization Who This Book Is For Got data? Not sure what to make of it? This is the guide for you - whether you've been working with Tableau for years or are just beginning your adventure into business analytics. What You Will Learn Find out how to build effective visualizations and dashboards Prepare and clean your data so you can be sure Tableau is finding answers to your questions - not raising more problems Discover how to create advanced visualizations that explain complexity with clarity and style Dig deeper into your data with clustering and distribution models that allow you to analyze trends and make forecasts Learn how to use data storytelling to aid decision-making and strategy Share dashboards and visualizations to cultivate a culture where data is available and valued In Detail Tableau has for some time been one of the most popular Business Intelligence and data visualization tools available. Why? Because, quite simply, it's a tool that's responsive to the needs of modern businesses. But it's most effective when you know how to get what you want from it - it might make your business intelligent, but it isn't going to make you intelligent... We'll make sure you're well prepared to take full advantage of Tableau 10's new features. Whether you're an experienced data analyst that wants to explore 2016's new Tableau, or you're a beginner that wants to expand their skillset and bring a more professional and sharper approach to their organization, we've got you covered. Beginning with the fundamentals, such as data preparation, you'll soon learn how to build and customize your own data visualizations and dashboards, essential for high-level visibility and effective data storytelling. You'll also find out how to so trend analysis and forecasting using clustering and distribution models to inform your analytics. But it's not just about you - when it comes to data it's all about availability and access. That's why we'll show you how to share your Tableau visualizations. It's only once insights a...
    Note: Description based on online resource; title from cover (Safari, viewed October 31, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781786466358/?ar
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    Mastering QlikView data visualization : take your QlikView skills to the next level and master the art of creating visual data analysis for real business needs (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781782173267 , 1782173269
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Professional expertise distilled
    Keywords: Management information systems ; Business intelligence ; Computer programs ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Take your QlikView skills to the next level and master the art of creating visual data analysis for real business needs About This Book Explore how to create your own QlikView data laboratory and how to develop QlikView applications using agile project methods Implement advanced data visualization and analysis for common business requirements from the sales, finance, marketing, inventory, operations, and human resources departments Learn from real-life experience shared in this book that will give you the upper hand in your next QlikView project Who This Book Is For This book is intended for developers who want to go beyond their technical knowledge of QlikView and understand how to create analysis and data visualizations that solve real business needs. You should have a basic understanding of advanced QlikView functions. What You Will Learn Apply advanced QlikView techniques such as set analysis and nested aggregation in order to deliver common business requirements Understand real business requirements for sales, finance, marketing, and human resources departments Discover when to apply more advanced data visualization such as frequency polygons, bullet graphs, and XmR charts Go beyond native QlikView and include geographical analysis, planning, and sentiment analysis in your QlikView application Troubleshoot common errors we discover at the moment we visualize data in QlikView Develop a plan to master Qlik Sense data visualization In Detail Just because you know how to swing a hammer doesn't mean you know how to build a house. Now that you've learned how to use QlikView, it's time to learn how to develop meaningful QlikView applications that deliver what your business users need. You will explore the requirements and the data from several business departments in order to deliver the most amazing analysis and data visualizations. In doing so, you will practice using advanced QlikView functions, chart object property options, and extensions to solve real-world challenges. Style and approach This hands-on guide follows the story of a company implementing QlikView as its enterprise data discovery solution. Each chapter starts with an understanding of the business requirements and the data model, and then helps you create insightful analysis and data visualizations. Each chapter expands on what was done in the previous chapter as we follow this continuously improving iterative process.
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed May 6, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781782173250/?ar
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    Mastering data visualization with Microsoft Visio Professional 2016 : master the art of presenting information visually using Microsoft Visio Professional 2016 and Visio Pro for Office365 = Master the art of presenting information visually using Microsoft Visio Professional 2016 and Visio Pro for Office365 (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785882821 , 1785882821
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Professional expertise distilled
    DDC: 005.4
    Keywords: Microsoft Visio ; Microsoft Visio ; Computer graphics ; Information visualization ; COMPUTERS / Data Visualization ; Computer graphics Software ; Information visualization
    Note: Description based on online resource; title from cover (Safari, viewed June 10, 2016). - Includes index
    URL: https://learning.oreilly.com/library/view/-/9781785882661/?ar
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    Python data science essentials : become an efficient data science practitioner by understanding Python's key concepts (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786462831 , 1786462834
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Database management ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Become an efficient data science practitioner by understanding Python's key concepts About This Book Quickly get familiar with data science using Python 3.5 Save time (and effort) with all the essential tools explained Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience Who This Book Is For If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills. What You Will Learn Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux Get data ready for your data science project Manipulate, fix, and explore data in order to solve data science problems Set up an experimental pipeline to test your data science hypotheses Choose the most effective and scalable learning algorithm for your data science tasks Optimize your machine learning models to get the best performance Explore and cluster graphs, taking advantage of interconnections and links in your data In Detail Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. Dive into building your essential Python 3.5 data science toolbox, using a single-source approach that will allow to to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and all the techniques you need to load, analyse, and process your data. Finally, get a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users. Style and approach The book is structured as a data science project. You will always benefit from clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
    Note: Previous edition published: 2015. - Description based on online resource; title from cover (Safari, viewed November 10, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781786462138/?ar
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    Simulation for data science with R : harness actionable insights from your data with computational statistics and simulations using R (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785885877 , 1785885871
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: R (Computer program language) ; Data mining ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Harness actionable insights from your data with computational statistics and simulations using R About This Book Learn five different simulation techniques (Monte Carlo, Discrete Event Simulation, System Dynamics, Agent-Based Modeling, and Resampling) in-depth using real-world case studies A unique book that teaches you the essential and fundamental concepts in statistical modeling and simulation Who This Book Is For This book is for users who are familiar with computational methods. If you want to learn about the advanced features of R, including the computer-intense Monte-Carlo methods as well as computational tools for statistical simulation, then this book is for you. Good knowledge of R programming is assumed/required. What You Will Learn The book aims to explore advanced R features to simulate data to extract insights from your data. Get to know the advanced features of R including high-performance computing and advanced data manipulation See random number simulation used to simulate distributions, data sets, and populations Simulate close-to-reality populations as the basis for agent-based micro-, model- and design-based simulations Applications to design statistical solutions with R for solving scientific and real world problems Comprehensive coverage of several R statistical packages like boot, simPop, VIM, data.table, dplyr, parallel, StatDA, simecol, simecolModels, deSolve and many more. In Detail Data Science with R aims to teach you how to begin performing data science tasks by taking advantage of Rs powerful ecosystem of packages. R being the most widely used programming language when used with data science can be a powerful combination to solve complexities involved with varied data sets in the real world. The book will provide a computational and methodological framework for statistical simulation to the users. Through this book, you will get in grips with the software environment R. After getting to know the background of popular methods in the area of computational statistics, you will see some applications in R to better understand the methods as well as gaining experience of working with real-world data and real-world problems. This book helps uncover the large-scale patterns in complex systems where interdependencies and variation are critical. An effective simulation is driven by data generating processes that accurately reflect real physical populations. You will learn how to plan and structure a simulation project to ai...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed July 20, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781785881169/?ar
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    Mastering IPython 4.0 : get to grips with the advanced concepts of interactive computing to make the most out of IPython (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785884153 , 1785884158
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Python (Computer program language) ; Parallel programming (Computer science) ; Information visualization ; Interactive computer systems ; Electronic books ; Electronic books ; local
    Abstract: Get to grips with the advanced concepts of interactive computing to make the most out of IPython About This Book Most updated book on Interactive computing with IPython 4.0; Detailed, example-rich guide that lets you use the most advanced level interactive programming with IPython; Get flexible interactive programming with IPython using this comprehensive guide Who This Book Is For This book is for IPython developers who want to make the most of IPython and perform advanced scientific computing with IPython utilizing the ease of interactive computing. It is ideal for users who wish to learn about the interactive and parallel computing properties of IPython 4.0, along with its integration with third-party tools and concepts such as testing and documenting results. What You Will Learn Develop skills to use IPython for high performance computing (HPC) Understand the IPython interactive shell Use XeroMQ and MPI to pass messages Integrate third-party tools like R, Julia, and JavaScript with IPython Visualize the data Acquire knowledge to test and document the data Get to grips with the recent developments in the Jupyter notebook system In Detail IPython is an interactive computational environment in which you can combine code execution, rich text, mathematics, plots, and rich media. This book will get IPython developers up to date with the latest advancements in IPython and dive deep into interactive computing with IPython. This an advanced guide on interactive and parallel computing with IPython will explore advanced visualizations and high-performance computing with IPython in detail. You will quickly brush up your knowledge of IPython kernels and wrapper kernels, then we'll move to advanced concepts such as testing, Sphinx, JS events, interactive work, and the ZMQ cluster. The book will cover topics such as IPython Console Lexer, advanced configuration, and third-party tools. By the end of this book, you will be able to use IPython for interactive and parallel computing in a high-performance computing environment. Style and approach This is a comprehensive guide to IPython for interactive, exploratory and parallel computing. It will let the IPython get up to date with the latest advancements in IPython and dive deeper into interactive computing with IPython
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed June 22, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781785888410/?ar
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    Learning Jupyter : learn how to write code, mathematics, graphics, and output, all in a single document as well as in a web browser using Project Jupyter (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785889455 , 1785889451
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Science ; Data processing ; Data mining ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Learn how to write code, mathematics, graphics, and output, all in a single document, as well as in a web browser using Project Jupyter About This Book Learn to write, execute, and comment your live code and formulae all under one roof using this unique guide This one-stop solution on Project Jupyter will teach you everything you need to know to perform scientific computation with ease This easy-to-follow, highly practical guide lets you forget your worries in scientific application development by leveraging big data tools such as Apache Spark, Python, R etc Who This Book Is For This book caters to all developers, students, or educators who want to execute code, see output, and comment all in the same document, in the browser. Data science professionals will also find this book very useful to perform technical and scientific computing in a graphical, agile manner. 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 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 in the same Notebook Organize your Notebook using Jupyter namespaces Access big data in Jupyter In Detail Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It 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, machine learning, and much more. This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next we'll help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode. Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book. Style and approach This comprehensive practical guide will teach you how to work with the Jupyter Notebook system. It demonstrates the integration of various programming languages with Jupyter Noteb...
    Note: Description based on online resource; title from cover (Safari, viewed January 5, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781785884870/?ar
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    Julia for data science : explore the world of data science from scratch with Julia by your side (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781783553860 , 1783553863
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Julia (Computer program language) ; Data structures (Computer science) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Explore the world of data science from scratch with Julia by your side About This Book An in-depth exploration of Julia's growing ecosystem of packages Work with the most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn about deep learning using Mocha.jl and give speed and high performance to data analysis on large data sets Who This Book Is For This book is aimed at data analysts and aspiring data scientists who have a basic knowledge of Julia or are completely new to it. The book also appeals to those competent in R and Python and wish to adopt Julia to improve their skills set in Data Science. It would be beneficial if the readers have a good background in statistics and computational mathematics. What You Will Learn Apply statistical models in Julia for data-driven decisions Understanding the process of data munging and data preparation using Julia Explore techniques to visualize data using Julia and D3 based packages Using Julia to create self-learning systems using cutting edge machine learning algorithms Create supervised and unsupervised machine learning systems using Julia. Also, explore ensemble models Build a recommendation engine in Julia Dive into Julia's deep learning framework and build a system using Mocha.jl In Detail Julia is a fast and high performing language that's perfectly suited to data science with a mature package ecosystem and is now feature complete. It is a good tool for a data science practitioner. There was a famous post at Harvard Business Review that Data Scientist is the sexiest job of the 21st century. (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century). This book will help you get familiarised with Julia's rich ecosystem, which is continuously evolving, allowing you to stay on top of your game. This book contains the essentials of data science and gives a high-level overview of advanced statistics and techniques. You will dive in and will work on generating insights by performing inferential statistics, and will reveal hidden patterns and trends using data mining. This has the practical coverage of statistics and machine learning. You will develop knowledge to build statistical models and machine learning systems in Julia with attractive visualizations. You will then delve into the world of Deep learning in Julia and will understand the framework, Mocha.jl with which you can create artificial neural networks and implement deep learning. T...
    Note: Description based on online resource; title from cover (Safari, viewed October 19, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781785289699/?ar
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    Hands-on data analysis with NumPy and Pandas : implement Python packages from data manipulation to processing (2016)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789534245 , 1789534240
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Numerical analysis ; Data processing ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Get to grips with the most popular Python packages that make data analysis possible About This Book Explore the tools you need to become a data analyst Discover practical examples to help you grasp data processing concepts Walk through hierarchical indexing and grouping for data analysis Who This Book Is For Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book. What You Will Learn Understand how to install and manage Anaconda Read, sort, and map data using NumPy and pandas Find out how to create and slice data arrays using NumPy Discover how to subset your DataFrames using pandas Handle missing data in a pandas DataFrame Explore hierarchical indexing and plotting with pandas In Detail Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python's NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python's pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation. Style and approach A step-by-step approach, taking you through the different concepts and features of Data Analysis using Python libraries and tools.
    Note: Description based on online resource; title from title page (Safari, viewed August 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789530797/?ar
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    Learning ELK stack : build mesmerizing visualizations, and analytics from your logs and data using Elasticsearch, Logstash, and Kibana (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785886706 , 1785886703
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Information visualization ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Build mesmerizing visualizations, analytics, and logs from your data using Elasticsearch, Logstash, and Kibana About This Book Solve all your data analytics problems with the ELK stack Explore the power of Kibana4 search and visualizations built over Elasticsearch queries and learn about the features and plugins of Logstash Develop a complete data pipeline using the ELK stack Who This Book Is For If you are a developer or DevOps engineer interested in building a system that provides amazing insights and business metrics out of data sources, of various formats and types, using the open source technology stack that ELK provides, then this book is for you. Basic knowledge of Unix or any programming language will be helpful to make the most out of this book. What You Will Learn Install, configure, and run Elasticsearch, Logstash, and Kibana Understand the need for log analytics and the current challenges in log analysis Build your own data pipeline using the ELK stack Familiarize yourself with the key features of Logstash and the variety of input, filter, and output plugins it provides Build your own custom Logstash plugin Create actionable insights using charts, histograms, and quick search features in Kibana4 Understand the role of Elasticsearch in the ELK stack In Detail The ELK stack - Elasticsearch, Logstash, and Kibana, is a powerful combination of open source tools. Elasticsearch is for deep search and data analytics. Logstash is for centralized logging, log enrichment, and parsing. Kibana is for powerful and beautiful data visualizations. In short, the Elasticsearch ELK stack makes searching and analyzing data easier than ever before. This book will introduce you to the ELK (Elasticsearch, Logstash, and Kibana) stack, starting by showing you how to set up the stack by installing the tools, and basic configuration. You'll move on to building a basic data pipeline using the ELK stack. Next, you'll explore the key features of Logstash and its role in the ELK stack, including creating Logstash plugins, which will enable you to use your own customized plugins. The importance of Elasticsearch and Kibana in the ELK stack is also covered, along with various types of advanced data analysis, and a variety of charts, tables ,and maps. Finally, by the end of the book you will be able to develop full-fledged data pipeline using the ELK stack and have a solid understanding of the role of each of the components. Style and approach This book is a step-by-...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed December 14, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781785887154/?ar
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    Creating data stories with Tableau Public : illustrate your data in a more interactive and interesting way using Tableau Public (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781849694773 , 184969477X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Tableau (Computer file) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Illustrate your data in a more interactive and interesting way using Tableau Public About This Book Learn the basics of creating visualizations with Tableau using this concise reference book Understand how to join and aggregate your data sources using Tableau It is a step by step guide that uses examples to help you understand the key concepts and feature of Tableau Public Who This Book Is For This book is targeted at investigative journalists and bloggers with an interest in making rich and interactive data visualizations. Intermediate Tableau Public users and organizations can also use this book as a reference guide and teaching aid. Members of the media team, such as data specialists, web developers, editors, producers, and managers can also benefit from an understanding of the structure and challenges of writing an interactive and interesting data visualization using Tableau Public. What You Will Learn Connect to various data sources and understand what data is appropriate for Tableau Public Understand chart types and when to use specific chart types with different types of data Join and aggregate data for use in Tableau Public data stories Discover features of Tableau Public, from basic to advanced Involve calculations in Tableau Public Build geographic maps to bring context to data Create dashboards from one or more separate data visualizations Create filters and actions to allow greater interactivity to Tableau Public visualizations and dashboards Publish and embed Tableau visualizations and dashboards in articles In Detail Tableau Public is a very useful tool in anyone's data reporting toolbox that allows authors to add an interactive data element to any article. It allows investigative journalists and bloggers to tell a ?data story?, allowing others to explore your data visualization. The relative ease of Tableau Public visualization creation allows data stories to be developed rapidly. It allows readers to explore data associations in multiple-sourced public data, and uses state-of-the-art dashboard and chart graphics to immerse the users in an interactive experience. This book offers investigative journalists, bloggers, and other data story tellers a rich discussion of visualization creation topics, features, and functions. This book allows data story tellers to quickly gain confidence in understanding and expanding their visualization-creation knowledge, and allows them to quickly create interesting, interactive data visualizations...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed December 15, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781849694766/?ar
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    Learning Tableau : leverage the power of Tableau 9.0 to design rich data visualizations and build fully interactive dashboards (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781784394349 , 1784394343
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Tableau (Computer file) ; Information visualization ; Visual analytics ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Tableau 9.0 to design rich data visualizations and build fully interactive dashboards In Detail In the professional world, turning massive amounts of data into something that can be seen and understood is vitally important. This is where Tableau steps in. It has emerged as a clear leader in data visualization because it translates your actions into a database query and expresses the response graphically. It also has the unique ability to do ad hoc analysis of millions of rows of data in just a matter of seconds with Tableau's Data Engine. Tableau is a rare software platform that is intuitive and even fun to use, which also enables you to dive deep into answering complex questions about your data. Starting with creating your first dashboard in Tableau 9.0, this book will let you in on some useful tips and tricks, teach you to tell data stories using dashboards, and teach you how to share these data stories. Practical examples along with detailed explanations of how and why various techniques work will help you learn and master Tableau quickly. What You Will Learn Explore and analyze your data by creating basic and advanced data visualizations Fix data problems, enhance your analysis, and create rich interactivity using custom calculations Perform effective analysis by joining and blending data from different sources Enhance your visualizations with custom formatting, labels, and annotations Explore advanced topics such as sheet swapping, custom maps, and LOD calculations Create meaningful dashboards in Tableau Extend the value and functionality of your data Share your data story using story points and fully interactive dashboards
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed May 12, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781784391164/?ar
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    Scala data analysis cookbook : navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781784394998 , 1784394998
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Quick answers to common problems
    Keywords: Data mining ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes About This Book Implement Scala in your data analysis using features from Spark, Breeze, and Zeppelin Scale up your data anlytics infrastructure with practical recipes for Scala machine learning Recipes for every stage of the data analysis process, from reading and collecting data to distributed analytics Who This Book Is For This book shows data scientists and analysts how to leverage their existing knowledge of Scala for quality and scalable data analysis. What You Will Learn Familiarize and set up the Breeze and Spark libraries and use data structures Import data from a host of possible sources and create dataframes from CSV Clean, validate and transform data using Scala to pre-process numerical and string data Integrate quintessential machine learning algorithms using Scala stack Bundle and scale up Spark jobs by deploying them into a variety of cluster managers Run streaming and graph analytics in Spark to visualize data, enabling exploratory analysis In Detail This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you'll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX. Style and approach This book contains a rich set of recipes that covers the full spectrum of interesting data analysis tasks and will help you revolutionize your data analysis skills using Scala and Spark.
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed December 10, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781784396749/?ar
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    TIBCO spotfire--a comprehensive planner : create innovative enterprise-class informatics solutions using TIBCO Spotfire (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781782176411 , 1782176411
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Professional expertise distilled
    Keywords: Information visualization ; Visual analytics ; Electronic books ; Electronic books ; local
    Abstract: Create innovative enterprise-class informatics solutions using TIBCO Spotfire In Detail The need for agile business intelligence (BI) is growing daily, and TIBCO Spotfire combines a self-service feature set with essential enterprise governance capabilities to deliver analytics solutions. Spotfire is easy and intuitive to use and can also be a rewarding development environment for all BI users. Starting with data and visualization concepts, this book takes you through increasingly advanced topics toward the goal of becoming a professional analytics solution provider. It explains data and visualization concepts and follows through with practical examples, such as getting data into Spotfire and using its visualization features. You will learn to build sophisticated user interactivity frameworks and spatial analytics, and administer the Spotfire environment. This book ends with a case study on self-service BI and leaves you equipped to contribute to the demand for more agile BI. What You Will Learn Master core data concepts, model the source data, slice and dice dimensional data, and define metrics and key performance indicators Learn to deploy Spotfire's suite of visualization types effectively and intelligently Build user-friendly analytics frameworks with Spotfire text areas and property controls Understand the different ways Spotfire can be deployed, licensed, and administered Use Spotfire's location analytics capabilities to create interactive geographic and nongeographic spatial analyses Write IronPython scripts against the Spotfire API to tackle and solve challenging analysis framework requirements Combine all your newfound or enhanced data, visualization, and programming skills to build self-service business intelligence solutions Explore Spotfire's predictive analytics, mobile metrics, event analytics, and advanced data services capabilities
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed March 11, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781782176404/?ar
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    Kibana essentials : use the functionalities of Kibana to reveal insights from the data and build attractive visualizations and dashboards for real-world scenarios (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781784392444 , 1784392448
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Information visualization ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Use the functionalities of Kibana to discover data and build attractive visualizations and dashboards for real-world scenarios About This Book Perform real-time data analytics and visualizations, on streaming data, using Kibana Build beautiful visualizations and dashboards with simplicity and ease without any type of coding involved Learn all the core concepts as well as detailed information about each component used in Kibana Who This Book Is For Whether you are new to the world of data analytics and data visualization or an expert, this book will provide you with the skills required to use Kibana with ease and simplicity for real-time data visualization of streaming data. This book is intended for those professionals who are interested in learning about Kibana,its installations, and how to use it . As Kibana provides a user-friendly web page, no prior experience is required. What You Will Learn Understand the basic concepts of elasticsearch used in Kibana along with step by step guide to install Kibana in Windows and Ubuntu Explore the functionality of all the components used in Kibana in detail, such as the Discover, Visualize, Dashboard,and Settings pages Analyze data using the powerful search capabilities of elasticsearch Understand the different types of aggregations used in Kibana for visualization Create and build different types of amazing visualizations and dashboards easily Create, save, share, embed, and customize the visualizations added to the dashboard Customize and tweak the advanced settings of Kibana to ensure ease of use In Detail With the increasing interest in data analytics and visualization of large data around the globe, Kibana offers the best features to analyze data and create attractive visualizations and dashboards through simple-to-use web pages. The variety of visualizations provided, combined with the powerful underlying elasticsearch capabilities will help professionals improve their skills with this technology. This book will help you quickly familiarize yourself to Kibana and will also help you to understand the core concepts of this technology to build visualizations easily. Starting with setting up of Kibana and elasticsearch in Windows and Ubuntu, you will then use the Discover page to analyse your data intelligently. Next, you will learn to use the Visualization page to create beautiful visualizations without the need for any coding. Then, you will learn how to use the Dashboard page to create a dashboard ...
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed December 1, 2015)
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    Learning Qlik Sense : the official guide : get the most out of your Qlik Sense investment with the latest insight and guidance direct from the Qlik Sense team (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785884054 , 1785884050
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Professional expertise distilled
    Keywords: Management information systems ; Business intelligence ; Computer programs ; Information visualization ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Get the most out of your Qlik Sense investment with the latest insight and guidance direct from the Qlik Sense team About This Book Updated with new coverage on Qlik Cloud, Qlik Sense Modeling, and Extending the Qlik Analytic Platform. Get insider insight on Qlik Sense and its new approach to business intelligence Explore practical demonstrations for utilizing Qlik Sense to discover data for sales, human resources, and more Who This Book Is For Learning Qlik Sense®: The Official Guide Second Edition is for anyone seeking to understand and utilize the revolutionary new approach to business intelligence offered by Qlik Sense. Familiarity with the basics of business intelligence will be helpful when picking up this book, but not essential. What You Will Learn Understand the vision behind the creation of Qlik Sense, and the promise that data discovery offers to you and your organization Get to grips with the life cycle of a Qlik Sense application Load and manage your data for app creation Visualize your data with Qlik Sense's engaging and informative graphing Administer your Qlik Sense system and monitor its security Build efficient and responsive Associative Models Extend the Qlik Analytic Platform with the Dev Hub Optimize Qlik Sense for sales, human resources, and demographic data discovery In Detail The intuitive and powerful Qlik Sense visual analytics software allows anyone to engage in data discovery, to explore your data, and find meaningful insights to empower your business. Qlik Sense lets you easily create personalized reports and visualizations and reveal essential connections to show new opportunities from every angle. Written by members of the Qlik Sense team, this book is the official guide from Qlik to understanding and using their powerful new product with fully updated coverage to the latest features of the most modern edition of Qlik Sense. Benefit from the vision behind the development of Qlik Sense and get to grips with how Qlik Sense can empower you as a data discovery consumer. Learn how to create your own applications for Qlik Sense to customize it to meet your personal needs for business intelligence, and how to oversee and administer the Qlik Sense data architecture. Finally, explore utilizing Qlik Sense to uncover essential data, with practical examples on finding and visualizing intelligence for sales figures, human resources information, travel expense tracking, and demographic data discovery. Style and approach This b...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed January 21, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781785887161/?ar
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    Data visualization with D3 and AngularJS : build dynamic and interactive visualizations from real-world data with D3 on AngularJS (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781784395780 , 1784395781
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Information visualization ; Visual analytics ; AngularJS (Software framework) ; Software frameworks ; Electronic books ; Electronic books ; local
    Abstract: Build dynamic and interactive visualizations from real-world data with D3 on AngularJS In Detail Using D3.js, the powerful JavaScript toolkit for creating cross-platform vector graphics, you can now combine performance with maximum compatibility to build a web-based visualization and present data in an interactive and convenient way. We'll reach top-notch reusability and testability by combining D3 graphics with our favorite web application framework, AngularJS. This book teaches the basics of vector graphics, D3, and AngularJS integration, and then dives into controlling, manipulating, and filtering data. You will learn about the testability of components and how to implement custom interactions, filters, and controllers; discover how to parse and map data in D3.js; and get a grasp on drawing D3.js built-in shapes and curves. After reading the last few chapters, you'll be able to bring life to your visualizations with more features of D3.js such as interactions, animations, and transitions. You will finish your journey by implementing a parser for different server application logs and display them on a Google Analytics style interactive dashboard. What You Will Learn Design, implement, and integrate an interactive dashboard to visualize server logs in real time using D3 graphics Learn cross-platform vector graphics to implement a dashboard visualization Perform data-driven transformations on selected HTML and SVG nodes Map, group, and filter datasets and create scales and axes Modularize data visualization information into reusable components to seamlessly integrate them into an AngularJS application Load, parse, and preprocess external data and autoupdate the visualization Design various chart types such as scatter, line, bar, or area and extend built-in shapes Create custom animations and transitions for the visualization Implement interactions and controls for the visualization preserving two-way binding between D3 and AngularJS components
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed May 26, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781784398484/?ar
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    Python data visualization cookbook : over 70 recipes, based on the principal concepts of data visualization, to get you started with popular Python libraries (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781784394943 , 1784394947
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Edition: Second edition.
    Series Statement: Quick answers to common problems
    Keywords: Information visualization ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization About This Book Learn how to set up an optimal Python environment for data visualization Understand how to import, clean and organize your data Determine different approaches to data visualization and how to choose the most appropriate for your needs Who This Book Is For If you already know about Python programming and want to understand data, data formats, data visualization, and how to use Python to visualize data then this book is for you. What You Will Learn Introduce yourself to the essential tooling to set up your working environment Explore your data using the capabilities of standard Python Data Library and Panda Library Draw your first chart and customize it Use the most popular data visualization Python libraries Make 3D visualizations mainly using mplot3d Create charts with images and maps Understand the most appropriate charts to describe your data Know the matplotlib hidden gems Use plot.ly to share your visualization online In Detail Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python. Style and approach A step-by-step recipe based approach to data visualization. The topics are explained sequentially as cookbook recipes consisting of a code snippet and the resulting visualization.
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed December 15, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781784396695/?ar
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    Mastering data analysis with R : gain clear insights into your data and solve real-world data science problems with R--from data munging to modeling and visualization (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781783982035 , 1783982039
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Data mining ; R (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Gain sharp insights into your data and solve real-world data science problems with R-from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R's range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed October 21, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781783982028/?ar
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  • 67
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    Online Resource
    Mastering Python data visualization : generate effective results in a variety of visually appealing charts using the plotting packages in Python (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 1783988339 , 9781783988334
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Information visualization ; Visual analytics ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Generate effective results in a variety of visually appealing charts using the plotting packages in Python About This Book Explore various tools and their strengths while building meaningful representations that can make it easier to understand data Packed with computational methods and algorithms in diverse fields of science Written in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed. What You Will Learn Gather, cleanse, access, and map data to a visual framework Recognize which visualization method is applicable and learn best practices for data visualization Get acquainted with reader-driven narratives and author-driven narratives and the principles of perception Understand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with it Explore with various visualization choices how Python can be very useful in computation in the field of finance and statistics Get to know why Python is the second choice after Java, and is used frequently in the field of machine learning Compare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.js Discover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework,...
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed December 7, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781783988327/?ar
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