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  • Safari, an O’Reilly Media Company  (405)
  • Organisation for Economic Co-operation and Development
  • [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc.  (405)
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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (52 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With a new generation of services and frameworks, frontend and mobile developers can use their existing skill set to build full stack applications by leveraging the cloud. Developers can build robust applications with production-ready features such as authentication, APIs, data layers, machine learning, chatbots, and AR scenes more easily than ever by taking advantage of these new serverless and cloud technologies. This practical guide explains how. Nader Dabit, developer advocate at Amazon Web Services, shows developers how to build full stack applications using React, AWS, GraphQL, and the Amplify Framework. You’ll learn how to create and incorporate services into your client applications while exploring general best practices, deployment strategies, continuous integration and delivery, and rich media management along the way. Learn how to build applications that solve real problems Understand what is (and isn’t) possible when using these technologies Examine how authentication works—and learn the difference between authentication and authorization Discover how serverless functions work and why they’re important Use GraphQL in your application—and learn why it’s important Learn how to build full stack applications on AWS
    Note: Online resource; Title from title page (viewed November 25, 2020)
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  • 2
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (66 pages)
    Edition: 3rd edition
    Keywords: Electronic books ; local
    Abstract: Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s nonrelational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data
    Note: Online resource; Title from title page (viewed July 25, 2020)
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  • 3
    Language: English
    Pages: 1 online resource (600 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Can a system ever truly be considered reliable if it isn't fundamentally secure? In two previous O'Reilly books, experts from Google showed how reliability is fundamental to service design. Site Reliability Engineering and The Site Reliability Workbook demonstrated how and why a commitment to the entire service lifecycle enables organizations to successfully build, deploy, monitor, and maintain software systems. Security is also crucial to the design and operation of scalable systems in production, as it plays an important part in product quality, performance, reliability, and availability. In a world where most products are connected to the internet, and with cloud technologies and machine learning becoming more prevalent, enabling security by default is increasingly important. This book shares best practices to help an organization of any size design scalable and reliable systems that are fundamentally secure. It also offers insights into how teams across an organization can collaborate on security and reliability. Specifically, you'll learn about: Design Strategies Implementation and Operations Preparing for the Worst: Detection and Response Scaling Security and the Organization
    Note: Online resource; Title from title page (viewed March 25, 2020)
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  • 4
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    ISBN: 9781492043423 , 1492043427 , 9781492043409 , 1492043400
    Language: English
    Pages: 1 online resource (500 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als
    DDC: 005.12
    Keywords: Software architecture ; Software architecture Vocational guidance ; Electronic books ; local ; Architecture logicielle ; Architecture logicielle ; Orientation professionnelle ; Software architecture
    Abstract: Although salary surveys worldwide regularly identify software architect as one of the top ten best jobs, no decent guides exist to help developers become architects. Until now. This practical guide provides the first comprehensive overview of software architecture’s many aspects. You’ll examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics. Authors Neal Ford and Mark Richards help you learn through examples in a variety of popular programming languages, such as Java, C#, JavaScript, and others. You’ll focus on architecture principles with examples that apply across all technology stacks.
    Note: Online resource; Title from title page (viewed February 25, 2020)
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  • 5
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (300 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Every day, companies struggle to scale critical applications. As traffic volume and data demands increase, these applications become more complicated and brittle, exposing risks and compromising availability. And with the popularity of software as a service, scaling has never been more important. Updated with an expanded focus on modern architecture paradigms such as microservices and cloud computing, this practical guide provides techniques for building systems that can handle huge quantities of traffic, data, and demand without affecting the quality your customers expect. Author Lee Atchison shows architects, managers, and directors in both engineering andoperations organizations how to build applications at scale that run more smoothly and reliably and meet the needs of your customers. See how scaling affects the availability of your services, why that matters, and how to improve it Dive into a modern service-based application architecture that ensures high availability and reduces the effects of service failures Explore the Single Team Owned Service Architecture paradigm (STOSA)—a model for scaling your development organization as your application scales Understand, measure, and mitigate risk in your systems Use the cloud to build highly scalable applications
    Note: Online resource; Title from title page (viewed June 25, 2020)
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  • 6
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (800 pages)
    Edition: 3rd edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Want to create devices that interact with the physical world? This cookbook is perfect for anyone who wants to experiment with the popular Arduino microcontroller and programming environment. You’ll find more than 200 tips and techniques for building a variety of objects and prototypes such as IoT solutions, environmental monitors, location and position-aware systems, and products that can respond to touch, sound, heat, and light. You don’t need to have mastered Arduino or programming to get started. Updated for the Arduino 1.5 release, the recipes in this third edition include practical examples and guidance to help you begin, expand, and enhance your projects right away—whether you’re an engineer, designer, artist, student, or hobbyist. Get up to speed on the Arduino board and essential software concepts quickly Learn basic techniques for reading digital and analog signals Use Arduino with a variety of popular input devices and sensors Drive visual displays, generate sound, and control several types of motors Interact with devices that use remote controls, including TVs and appliances Learn techniques for handling time delays and time measurement Apply advanced coding and memory-handling techniques
    Note: Online resource; Title from title page (viewed April 25, 2020)
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  • 7
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (275 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. The book also explores new approaches for integrating data privacy into machine learning pipelines. Understand the machine learning management lifecycle Implement data pipelines with Apache Airflow and Kubeflow Pipelines Work with data using TensorFlow tools like ML Metadata, TensorFlow Data Validation, and TensorFlow Transform Analyze models with TensorFlow Model Analysis and ship them with the TFX Model Pusher Component after the ModelValidator TFX Component confirmed that the analysis results are an improvement Deploy models in a variety of environments with TensorFlow Serving, TensorFlow Lite, and TensorFlow.js Learn methods for adding privacy, including differential privacy with TensorFlow Privacy and federated learning with TensorFlow Federated Design model feedback loops to increase your data sets and learn when to update your machine learning models
    Note: Online resource; Title from title page (viewed August 25, 2020)
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  • 8
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (300 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Early system administration required in-depth knowledge of a variety of services on individual systems. Now, the job is increasingly complex and different from one company to the next with an ever-growing list of technologies and third-party services to integrate. How does any one individual stay relevant in systems and services? This practical guide helps anyone in operations—sysadmins, automation engineers, IT professionals, and site reliability engineers—understand the essential concepts of the role today. Collaboration, automation, and the evolution of systems change the fundamentals of operations work. No matter where you are in your journey, this book provides you the information to craft your path to advancing essential system administration skills. Author Jennifer Davis provides examples of modern practices and tools with recommended materials to advance your skills. Topics include: Development and testing: Version control, fundamentals of virtualization and containers, testing, and architecture reviewDeploying and configuring services: Infrastructure management, networks, security, storage, serverless, and release managementScaling administration: Monitoring and observability, capacity planning, log management and analysis, and security and compliance
    Note: Online resource; Title from title page (viewed July 25, 2020)
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  • 9
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (58 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als Yablonski, Jon Laws of UX
    RVK:
    Keywords: Electronic books ; local ; Webdesign ; Gebrauchsgrafik ; Mensch-Maschine-Kommunikation ; Benutzerfreundlichkeit ; Verhaltenspsychologie
    Abstract: Every designer today should learn the fundamentals of psychology. Instead of forcing users to conform to a product design or experience, designers need to learn how users behave and interact with various digital interfaces. This guide provides some key principles from psychology to help you design more intuitive, human-centered products and experiences. Humans have an underlying blueprint for how we perceive and process the world around us, and through simple lessons in psychology, this guide will help you define this blueprint.
    Note: Online resource; Title from title page (viewed April 25, 2020)
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  • 10
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (300 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With Early Release ebooks, you get books in their earliest form—the author's raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles. JavaScript is the little scripting language that could. Once used chiefly to add interactivity to web browser windows, JavaScript is now a primary building block of powerful and robust applications. In this practical book, new and experienced JavaScript developers will learn how to use this language to create APIs as well as web, mobile, and desktop applications. Author and engineering leader Adam D. Scott covers technologies such as Node.js, GraphQL, React, and React Native. Ideal for developers who want to build full stack applications and web development beginners looking to bootstrap a startup, this book shows you how to create a single CRUD-style application that will work across several platforms. Explore GraphQL's simple process for querying data Learn about shared authentication for APIs, web apps, and native applications Build universal web applications with React and Next.js that perform and render on the server Use React Native to write cross-platform applications for iOS and Android that compile to native code Learn how to write desktop applications with Electron
    Note: Online resource; Title from title page (viewed March 25, 2020)
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  • 11
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (51 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: While many resources for network and IT security are available, detailed knowledge regarding modern web application security has been lacking—until now. This practical guide provides both defensive and offensive security concepts that software engineers can easily learn and apply. Andrew Hoffman, a product security lead at Salesforce.com, introduces three pillars of web application security: recon, offense, and defense. You’ll learn methods for effectively researching and analyzing modern web applications—including those you don’t have direct access to. You’ll also learn how to apply countermeasures to your own applications in order to prevent or mitigate risk from hackers. Ideal as a reference guide or educational text, this book helps you: Explore common vulnerabilities that plague today's web applications Learn essential hacking techniques that attackers use for exploiting applications Map and document web applications for which you do not have direct access Hack your application by applying the OWASP 10 exploits and other attacks Learn how to code your application to protect against the attacks you’ve identified Get practical tips to help you improve the overall security of your web products Develop and deploy your own customized exploits that can bypass many defenses
    Note: Online resource; Title from title page (viewed June 25, 2020)
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  • 12
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (540 pages)
    Edition: 4th edition
    Keywords: Electronic books ; local
    Abstract: Why is PHP the most widely used programming language on the web? This updated edition teaches everything you need to know to create effective web applications using the latest features in PHP 7.3. You’ll start with the big picture and then dive into language syntax, programming techniques, and other details, using examples that illustrate both correct usage and common idioms. If you have a working knowledge of HTML and CSS, authors Kevin Tatroe and Peter MacIntyre provide style tips and practical programming advice in a clear, concise manner to help you become a top-notch PHP programmer. Get an overview of what’s possible when you use PHP programs Learn language fundamentals, including data types, variables, operators, and flow control statements Explore functions, strings, arrays, and objects Apply common web application techniques, such as form processing, data validation, session tracking, and cookies Interact with relational databases like MySQL or NoSQL databases such as MongoDB Generate dynamic images, create PDF files, and parse XML files Learn secure scripts, error handling, performance tuning, and other advanced topics Get a quick reference to PHP core functions and standard extensions
    Note: Online resource; Title from title page (viewed April 25, 2020)
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  • 13
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (375 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: If you want to build, iterate and scale NLP systems in a business setting and to tailor them for various industry verticals, this is your guide. Consider the task of building a chatbot or text classification system at your organization. In the beginning, there may be little or no data to work with. At this point, a basic solution that uses rule based systems or traditional machine learning will be apt. As you accumulate more data, more sophisticated—and often data intensive—ML techniques can be used including deep learning. At each step of this journey, there are dozens of alternative approaches you can take. This book helps you navigate this maze of options.
    Note: Online resource; Title from title page (viewed May 25, 2020)
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  • 14
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (224 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Serverless is a revolution in the way organizations build and deploy software. With this hands-on guide, Java engineers will learn how to use their language experience in the new world of serverless computing. You’ll discover how this cloud computing model can drastically reduce the complexity in developing and operating applications while reducing costs and time to market. Engineering leaders John Chapin and Mike Roberts guide you through the process of developing serverless applications using AWS Lambda, Amazon’s event-driven, serverless computing platform. You’ll learn how to prepare the development environment, program Lambda functions, and deploy and operate your serverless software. Chapters includes exercises to help you through each aspect of the process. Get an introduction to serverless, functions-as-a-service, and AWS Lambda Learn how to deploy working Lambda functions to the cloud Program Lambda functions and learn how to get data in and out Build and package Java-based Lambda code and dependencies Create serverless applications by building a serverless API and data pipeline Test your serverless applications using automated techniques Apply advanced techniques to build production-ready applications
    Note: Online resource; Title from title page (viewed February 25, 2020)
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  • 15
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (50 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: The future will be increasingly decentralized. As the publicity surrounding bitcoin and blockchain has shown, decentralized technology and distributed business models are already popular. Yet the disruptive potential of this technology is obscured by hype and misconceptions in equal measure. In this detailed guide, Lorne Lantz and Daniel Cawrey distill the complex ideas behind blockchain into an easily digestible reference that shows what is really going on under the hood. Finance and technology professionals will learn how a blockchain works as they explore the evolution and current state of cryptocurrencies, and the function of smart contracts. If you’re evaluating whether to invest your time in the cryptocurrency and blockchain industry, this book is for you. Get beyond the buzzwords and discover what the technology has to offer. Learn why Bitcoin was fundamentally important to the birth of blockchain Explore altcoin and altchain successes and failures, to see what can be done with blockchains and cryptocurrencies Understand the challenges of scaling a blockchain and forking a blockchain project See what Ethereum offers beyond Bitcoin Examine how the money flows in crypto markets Discover why, how, and where governments are intervening in the cryptocurrency and blockchain industry Understand the perspectives of real-world practitioners in the space
    Note: Online resource; Title from title page (viewed October 25, 2020)
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  • 16
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (232 pages)
    Edition: 7th edition
    Keywords: Electronic books ; local
    Abstract: For web developers and other programmers interested in using JavaScript, this bestselling book provides the most comprehensive JavaScript reference section on the market. The seventh edition represents a significant update, with new material for ECMAScript 2017 (ES8), and new chapters on language-specific features. JavaScript: The Definitive Guide is ideal for experienced programmers who want to learn the programming language of the web, and for current JavaScript programmers who want to master it.
    Note: Online resource; Title from title page (viewed July 25, 2020)
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  • 17
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (87 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Your Python code may run correctly, but you need it to run faster. By exploring the fundamental theory behind design choices, the updated edition of this practical guide, expanded and enhanced for Python 3, helps you gain a deeper understanding of Python’s implementation. You’ll learn how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. How can you take advantage of multicore architectures or clusters? Or build a system that can scale up and down without losing reliability? Experienced Python programmers and students alike will learn concrete solutions to these and other issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and other situations. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Understand performant pandas Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix, vector, and even tensor computations Use tools to compile Python down to machine code, on CPUs and GPUs Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on a local or remote cluster Deploy code faster using tools like Docker Solve large problems while using less RAM Get real-life stories and lessons from Python programmers
    Note: Online resource; Title from title page (viewed June 25, 2020)
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  • 18
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (300 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Data is getting bigger, arriving faster, and coming in varied formats—and it all needs to be processed at scale for analytics or machine learning. How can you process such varied data workloads efficiently? Enter Apache Spark. Updated to emphasize new features in Spark 2.x., this second edition shows data engineers and scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine-learning algorithms. Through discourse, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level APIs: DataFrames and Datasets Peek under the hood of the Spark SQL engine to understand Spark transformations and performance Inspect, tune, and debug your Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow Use open source Pandas framework Koalas and Spark for data transformation and feature engineering
    Note: Online resource; Title from title page (viewed June 25, 2020)
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  • 19
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (350 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Most applications today are distributed in some fashion. Monitoring the health and performance of these distributed architectures requires a new approach. Enter distributed tracing, a method of profiling and monitoring applications—especially those that use microservice architectures. There’s just one problem: distributed tracing can be hard. But it doesn’t have to be. With this practical guide, you’ll learn what distributed tracing is and how to use it to understand the performance and operation of your software. Key players at LightStep walk you through instrumenting your code for tracing, collecting the data that your instrumentation produces, and turning it into useful, operational insights. If you want to start implementing distributed tracing, this book tells you what you need to know. You’ll learn: The pieces of a distributed tracing deployment: Instrumentation, data collection, and delivering value Best practices for instrumentation (the methods for generating trace data from your service) How to deal with or avoid overhead, costs, and sampling How to work with spans (the building blocks of request-based distributed traces) and choose span characteristics that lead to valuable traces Where distributed tracing is headed in the future
    Note: Online resource; Title from title page (viewed June 25, 2020)
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  • 20
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (93 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this practical guide—now including examples in Python as well as R—explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not. Many data scientists use statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages, and have had some exposure to statistics but want to learn more, this quick reference bridges the gap in an accessible, readable format. With this updated edition, you’ll dive into: Exploratory data analysis Data and sampling distributions Statistical experiments and significance testing Regression and prediction Classification Statistical machine learning Unsupervised learning
    Note: Online resource; Title from title page (viewed May 25, 2020)
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  • 21
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (94 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: If you want to build an enterprise-quality application that uses natural language text, but aren’t sure where to begin or what tools to use, this practical guide will help get you started. You’ll explore special concerns for developing text-based applications, such as performance. Alex Thomas, data scientist at Indeed, shows software engineers and data scientists how to build scalable NLP applications using deep learning and the Apache Spark NLP library. Through concrete examples, practical and theoretical explanations, and hands-on exercises for using NLP on the Spark processing framework, this book teaches you everything from NLP basics to applications of powerful modern techniques. Process text in a distributed environment using Spark NLP, a production-ready library for NLP built on Spark Create, tune, and deploy your own word embeddings Adapt your NLP applications to multiple languages Use text in machine learning and deep learning Learn why these techniques work from a machine learning, linguistic, and practical point of view
    Note: Online resource; Title from title page (viewed July 25, 2020)
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  • 22
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (37 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Learn how to build a serverless real-world application in the cloud that’s reliable, secure, maintainable, and can handle millions of users. If you have experience building traditional web applications, this practical guide shows you how to get started with serverless. Cloud engineer Wietse Venema takes you through the steps necessary to build serverless applications with Cloud Run, a container-based serverless platform on Google Cloud. Through the course of the book, you’ll learn how to become productive with serverless technology. You will build and explore several example applications that highlight different parts of the serverless stack, using (light) frontend technology and Go on the back end. You can also follow the lessons in the book using your own project on Google Cloud Platform. You’ll learn how to: Build a serverless application with Google’s Cloud Run and Firestore Approach testing and development Handle user management and authentication Combine serverless with a traditional relational database Run and monitor production services Integrate your application with external APIs
    Note: Online resource; Title from title page (viewed July 25, 2020)
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  • 23
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (210 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: How can startups successfully scale customer acquisition and revenue growth with a lean team? Out-of-the-box acquisition solutions from Facebook, Google, and others provide a good start, but the companies that can tailor those solutions to meet their specific needs, objectives, and goals will come out winners. With this practical book, author Lomit Patel shows you how to use AI and machine learning (ML) to provide an operational layer atop those acquisition solutions to deliver meaningful results for your company. You’ll learn how to adapt, customize, and personalize cross-channel user journeys to help your company attract and maintain customers. Learn how AI and ML can support the customer acquisition efforts of a lean startup Dive into Customer Acquisition 3.0, an initiative for gaining and retaining customers Explore ways to use ML for marketing purposes Understand the key metrics for determining the growth of your startup Determine the right strategy to foster user acquisition in your company Manage the increased complexity and risk inherent in AI projects
    Note: Online resource; Title from title page (viewed March 25, 2020)
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  • 24
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (600 pages)
    Edition: 4th edition
    Keywords: Electronic books ; local
    Abstract: Java continues to grow and evolve, and this Cookbook continues to evolve in tandem. This book helps to get you up to speed right away with hundreds of hands-on recipes across a broad range of Java topics. You’ll learn useful techniques for everything from string handling and functional programming to network communication. Each recipe includes self-contained code solutions that you can freely use, along with a discussion of how and why they work. If you are familiar with the basics of the Java language, this cookbook will bolster your knowledge of the language in general and its many recent changes and how to apply them in your day-to-day development. Recipes include: Methods for compiling, running, and debugging “Packaging” Java classes and building applications Manipulating, comparing, and rearranging text Regular expressions for string- and pattern-matching Handling numbers, dates, and times Structuring data with collections, arrays, and other types Object-oriented and functional programming techniques Input/Output, Directory and filesystem operations Network programming on both client and server Processing JSON for data interchange Multithreading and concurrency Using Java in Big Data applications Interfacing Java with other languages The 4th Edition of this book has been updated to cover changes through Java 12 and includes new recipes for Big Data and data science.
    Note: Online resource; Title from title page (viewed April 25, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (250 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With Early Release ebooks, you get books in their earliest form—the authors' raw and unedited content as they write—so you can take advantage of these technologies long before the official release of these titles. This book will enable you to apply graph thinking to solve complex problems. If you want to learn how to build architectures for extracting value for your domain’s complex problems, then this book is for you. You’ll learn how to think about your data as a graph, and how to determine if graph technology is right for your application. The book describes techniques for scalable, real-time, and multimodel architectures that solve complex problems, and shows how companies are successfully applying graph thinking in distributed production environments. Authors Denise Koessler Gosnell and Matthias Broecheler also introduce the Graph Schema Language, a set of terminology and visual illustrations to normalize how graph practitioners communicate conceptual graph models, graph schema, and graph database design.
    Note: Online resource; Title from title page (viewed April 25, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (250 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the tools, best practices, and challenges involved in building a real-world ML application step-by-step. Author Emmanuel Ameisen, who worked as a data scientist at Zipcar and led Insight Data Science’s AI program, demonstrates key ML concepts with code snippets, illustrations, and screenshots from the book’s example application. The first part of this guide shows you how to plan and measure success for an ML application. Part II shows you how to build a working ML model, and Part III explains how to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies. This book will help you: Determine your product goal and set up a machine learning problem Build your first end-to-end pipeline quickly and acquire an initial dataset Train and evaluate your ML model and address performance bottlenecks Deploy and monitor models in a production environment
    Note: Online resource; Title from title page (viewed February 25, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (150 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: If you’re among the Python developers put off by Asyncio’s complexity, it’s time to take another look. Asyncio is complicated because it aims to solve problems in concurrent network programming for both framework developers and end-user developers like you. The features you need to consider are a small subset of the whole Asyncio API, but picking out the right features is the tricky part. That’s where this practical book comes in. Veteran Python developer Caleb Hattingh helps end-user developers gain a basic understanding of Asyncio’s building blocks—enough to get you started writing simple event-based programs. You’ll learn why Asyncio offers a safer alternative to preemptive multitasking (threading) and how this API provides a simple way to support thousands of simultaneous socket connections. Get a critical comparison of Asyncio and threading for concurrent network programming Take an Asyncio walkthrough, including a quickstart guide to help you hit the ground looping with event-based programming Learn the difference between Asyncio features for end-user developers and those for framework developers Understand Asyncio’s new async/await language syntax, including coroutines and task and future APIs Get detailed case studies (with code) of some popular Asyncio-compatible third-party libraries
    Note: Online resource; Title from title page (viewed March 25, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (200 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Threat modeling is one of the most essential—and most misunderstood—parts of the development lifecycle. Whether you’re a security practitioner or application developer, this book will help you gain a better understanding of core concepts and how to apply them to your practice to protect your systems from threats. Authors Izar Tarandach and Matthew Coles walk you through the myriad ways to approach and execute threat modeling. Contrary to popular belief, the process takes neither incredibly advanced security knowledge nor an unmanageable amount of effort. But it’s critical for spotting and addressing potential concerns in a cost-effective way before the code’s written and it’s too late to find a solution. Find out why threat modeling is important and how it can make you and your team better, more well-rounded architects and developers Learn the most effective ways to integrate threat modeling into your development lifecycle Use the results of a threat modeling exercise on other aspects of the system lifecycle
    Note: Online resource; Title from title page (viewed April 25, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (150 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Operators are a way of packaging, deploying, and managing Kubernetes applications. A Kubernetes application doesn’t just run on Kubernetes; it’s composed and managed in Kubernetes terms. Operators add application-specific operational knowledge to a Kubernetes cluster, making it easier to automate complex, stateful applications and to augment the platform. Operators can coordinate application upgrades seamlessly, react to failures automatically, and streamline repetitive maintenance like backups. Think of Operators as site reliability engineers in software. They work by extending the Kubernetes control plane and API, helping systems integrators, cluster administrators, and application developers reliably deploy and manage key services and components. Using real-world examples, authors Jason Dobies and Joshua Wood demonstrate how to use Operators today and how to create Operators for your applications with the Operator Framework and SDK. Learn how to establish a Kubernetes cluster and deploy an Operator Examine a range of Operators from usage to implementation Explore the three pillars of the Operator Framework: the Operator SDK, the Operator Lifecycle Manager, and Operator Metering Build Operators from the ground up using the Operator SDK Build, package, and run an Operator in development, testing, and production phases Learn how to distribute your Operator for installation on Kubernetes clusters
    Note: Online resource; Title from title page (viewed March 25, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (280 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: As Python continues to grow in popularity, projects are becoming larger and more complex. Many Python developers are now taking an interest in high-level software architecture patterns such as hexagonal/clean architecture, event-driven architecture, and strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Python isn’t always straightforward. With this practical guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexity. Each pattern is illustrated with concrete examples in idiomatic Python that explain how to avoid some of the unnecessary verbosity of Java and C# syntax. You’ll learn how to implement each of these patterns in a Pythonic way. Architectural design patterns include: Dependency inversion, and its links to ports and adapters (hexagonal/clean architecture) Domain-driven design’s distinction between entities, value objects, and aggregates Repository and Unit of Work patterns for persistent storage Events, commands, and the message bus Command Query Responsibility Segregation (CQRS) Event-driven architecture and reactive microservices
    Note: Online resource; Title from title page (viewed April 25, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (451 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout all these transformations, Python has become one of the most popular languages in the world. This practical guide shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is an essential skill for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. If you’re looking for effective ways to "get stuff done" in Python, this is your guide. Automate several tasks using Python Work more efficiently by using a smaller subset of the language Use continuous integration systems to increase software quality Mix shell and Python commands to solve problems
    Note: Online resource; Title from title page (viewed January 3, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (450 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Coding and testing are generally considered separate areas of expertise. In this practical book, Java expert Scott Oaks takes the approach that anyone who works with Java should be equally adept at understanding how code behaves in the Java Virtual Machine—including the tunings likely to help performance. This updated second edition helps you gain in-depth knowledge of Java application performance using both the JVM and the Java platform. Developers and performance engineers alike will learn a variety of features, tools, and processes for improving the way Java 8 and 11 LTS releases perform. While the emphasis is on production-supported releases and features, this book also features previews of exciting new technologies such as ahead-of-time compilation and experimental garbage collections. Understand how various Java platforms and compilers affect performance Learn how Java garbage collection works Apply four principles to obtain best results from performance testing Use the JDK and other tools to learn how a Java application is performing Minimize the garbage collector’s impact through tuning and programming practices Tackle performance issues in Java EE and SE APIs Improve Java-driven database application performance
    Note: Online resource; Title from title page (viewed February 25, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (56 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Level up with Tableau to build eye-catching, easy-to-interpret data visualizations. In this follow-up guide to 2018’s Practical Tableau, author Ryan Sleeper takes you through a collection of unique tips and tutorials for using this popular software. Beginning to advanced Tableau users will learn how to go beyond Show Me to make better data charts and learn dozens of tricks to improve both the author and user experience. Featuring many tutorials he designed himself, Ryan shows you how to create charts that empower Tableau users to explore, understand, and derive value from their data. He also shares many of his favorite tricks that enabled him to become a Tableau Zen Master, Tableau Public Visualization of the Year author, and Tableau Iron Viz Champion. Learn what’s new in Tableau since Practical Tableau was released in 2018 Examine unique new charts—timelines, custom gauges, and leapfrog charts—plus innovations such as highlight tables, scatter plots, and maps Get tips that can help make a Tableau developer’s life easier Understand what developers can do to make users’ lives easier
    Note: Online resource; Title from title page (viewed July 25, 2020)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (848 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
    Note: Online resource; Title from title page (viewed September 30, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (36 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Your company creates terabytes and even petabytes of data, but are you actually putting it to work? The majority of enterprises stumble on their way to becoming data driven. Machine learning promises to reverse that trend, and early adopters are already seeing the benefits with increased ROI. In this report, author Alice LaPlante details successful real-world applications for machine learning and shows you how to implement your own machine learning initiative step-by-step. Discover how machine learning can benefit your business and see how companies such as CaixaBank and DX Marketing use machine learning to their advantage. Don’t fall behind while early adopters reap all the gains. Get started with machine learning and tame your data. You’ll learn: Machine learning use cases, including recommendation engines, fraud detection, predictive maintenance, and more The benefits of machine learning Why companies are increasingly moving machine learning implementations to the cloud The six phases of the machine learning lifecycle A five-step process to getting started with machine learning The challenges you may encounter along the way Best practices and advice from early adopters
    Note: Online resource; Title from title page (viewed November 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Over the past 10 years, big data infrastructure has evolved from flat files in a distributed filesystem to an efficient ecosystem to a fully deconstructed and open source database with reusable components. With Hadoop, we started from a system that was good at looking for a needle in a haystack using snowplows. We had a lot of horsepower and scalability but lacked the subtlety and efficiency of relational databases. But since Hadoop provided the ultimate flexibility compared to the more constrained and rigid RDBMSs, we didn’t mind and plowed through. However, machine learning, recommendations, matching, abuse detection, and data-driven products in general require a more flexible infrastructure. Over time, we started applying everything that had been known to the database world for decades to this new environment. We’d been told loud enough how Hadoop was a huge step backward. And it was true to some degree. The key difference was the flexibility of the Hadoop stack. There are many highly integrated components in a relational database and decoupling them took some time. Today, we see the emergence of key components, such as optimizers, columnar storage, in-memory representation, table abstraction, and batch and streaming execution, as standards that provide the glue between the options available to process, analyze, and learn from our data. We’ve been deconstructing the tightly integrated relational database into flexible reusable open source components. Storage, compute, multitenancy, and batch or streaming execution are all decoupled and can be modified independently to fit every use case. Julien Le Dem (WeWork) discusses the key open source components of the big data ecosystem—including Apache Calcite, Parquet, Arrow, Avro, and Kafka as well as batch and streaming systems—and explains how they relate to each other and how they make the ecosystem more of a database and less of a filesystem. (Parquet is the columnar data layout to optimize data at rest for querying. Arrow is the in-memory representation for maximum throughput execution and overhead-free data exchange. Calcite is the optimizer to make the most of our infrastructure capabilities.) Julien also explores the emerging components that are still missing or haven’t become standard yet to fully materialize the transformation to an extremely flexible database that lets you innovate with your data. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 40 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In many industrial ML applications, feature engineering consumes the lion’s share of time, energy, and resources. Deep learning promises to replace feature engineering with models that learn end to end from “close-to-reality” data and has convincingly realized this promise for computer vision and natural language processing. But does this promise apply outside of these domains? Pamela Vagata (Stripe) explains how Stripe has applied deep learning techniques to predict fraud from raw behavioral data. Since fraud detection is a critical business problem for Stripe, the company already had a well-tuned feature-engineered model for comparison. Stripe found that the deep learning model outperforms the feature-engineered model both on predictive performance and in the effort spent on data engineering, model construction, tuning, and maintenance. Join in to discover how common industry practice could shift toward deeper models trained end to end and away from labor-intensive feature engineering. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 38 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: We never change the amount of work or technical debt; we just shift it, and with it, we change how it emerges and appears. Our systems don’t have to be perfect to be operational—planes, networks, and elite athletes all function at extremely high levels even though they are not operating at 100%. As an industry, we have moved the locus of control from hardware to operating system to virtual machine to container to orchestration, and now we’re approaching serverless. None of that has reduced the amount of work you have to do; it just makes it so you can reuse and conceptually compress the work of others. Since we’re making the work in our tools less visible, we also have less control over how they work. We assume the promises that have been true will continue to be true, but that isn’t in our control. Heidi Waterhouse (LaunchDarkly) explains how to handle this level of uncertainty. You’ll learn to add in error budgets, layered access, and other accommodations for failure and to design your systems for function over form or purity. You’ll leave with some concrete ideas about how to add resiliency to your system by learning to trust but mitigate your reliance on perfect performance of your underlying tools. This session was recorded at the 2019 O'Reilly Velocity Conference in San Jose.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 50 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In his best-selling book Patterns of Enterprise Application Architecture , Martin Fowler famously coined the first law of distributed computing—"Don’t distribute your objects"—implying that working with this style of architecture can be challenging. A few years ago, Barclays embarked on a journey to migrate its legacy services with the objective of achieving a high level of scale, resilience, and reliability, mainly employing an ecosystem of focused, distributed services. It’s fair to say that the company has discovered through firsthand experience that there’s quite a bit of truth to that statement. Prem Chandrasekaran provides an insider scoop on Barclays’s journey deploying services to a private cloud-based infrastructure making use of foundational patterns such as domain-driven design, event-driven architecture (EDA), command query responsibility segregation (CQRS), and event sourcing, among others. Prem recounts some of the challenges faced during the transformation and sheds light on the things that worked well and those that didn’t. Topics include: How to establish buy-in with senior stakeholders and management How to recruit, onboard, and train new team members How to establish the boundaries of your teams and services How to focus on the right amount and kinds of tests in your pipelines How to ensure database and API compatibility How to centralize and externalize secrets and configuration How to diagnose and pinpoint issues in unattended, asynchronous processes How to decide between blue-green and rolling deployments How to work with private and public cloud implementations This session was recorded at the 2019 O'Reilly Software Architecture Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (500 pages)
    Edition: 3rd edition
    Keywords: Electronic books ; local
    Abstract: It's not easy to design good application interfaces in a world where companies must create compelling, seamless user experiences across an exploding number of channels, screens, and contexts. Design patterns, design systems, and component-based UI frameworks have emerged and now rapidly evolve to meet the challenge. This bestselling book is one of the few reliable sources to help you navigate through the maze of design options. By capturing UI best practices and reusable ideas as design patterns, Designing Interfaces provides solutions to common design problems that you can tailor to the situation at hand. This updated edition includes patterns for mobile apps and social media, as well as web applications and desktop software. Each pattern contains full-color examples and practical design advice that you can use immediately. Experienced designers can use this guide as a sourcebook of ideas; novices will find a roadmap to the world of interface and interaction design.
    Note: Online resource; Title from title page (viewed December 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 42 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Recommender systems support the decision making processes of customers with personalized suggestions. These widely used systems influence the daily life of almost everyone across domains like ecommerce, social media, and entertainment. However, the efficient generation of relevant recommendations in large-scale systems is a very complex task. In order to provide personalization, engines and algorithms need to capture users’ varying tastes and find mostly nonlinear dependencies between them and a multitude of items. Enormous data sparsity and ambitious real-time requirements further complicate this challenge. At the same time, deep learning has been proven to solve complex tasks like object or speech recognition where traditional machine learning failed or showed mediocre performance. Join Marcel Kurovski (inovex) to explore a use case for vehicle recommendations at mobile.de, Germany’s biggest online vehicle market. Marcel shares a novel regularization technique for the optimization criterion and evaluates it against various baselines. To achieve high scalability, he combines this method with strategies for efficient candidate generation based on user and item embeddings—providing a holistic solution for candidate generation and ranking. The proposed approach outperforms collaborative filtering and hybrid collaborative-content-based filtering by 73% and 143% for MAP5. It also scales well for millions of items and users returning recommendations in tens of milliseconds. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (120 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Data professionals are confronting the most disruptive change since relational databases appeared in the 1980s. SQL is still a major tool for data analytics, but conventional relational database management systems can’t handle the increasing size and complexity of today’s datasets. This updated edition teaches you best practices for Greenplum Database, the open source massively parallel processing (MPP) database that accommodates large sets of nonrelational and relational data. Marshall Presser, field CTO at Pivotal, introduces Greenplum’s approach to data analytics and data-driven decisions, beginning with its shared-nothing architecture. IT managers, developers, data analysts, system architects, and data scientists will all gain from exploring data organization and storage, data loading, running queries, and learning to perform analytics in the database. Discover how MPP and Greenplum will help you go beyond the traditional data warehouse. This ebook covers: Greenplum features, use case examples, and techniques for optimizing use Four Greenplum deployment options to help you balance security, cost, and time to usability Why each networked node in Greenplum’s architecture includes an independent operating system, memory, and storage Additional tools for monitoring, managing, securing, and optimizing query responses in the Pivotal Greenplum commercial database
    Note: Online resource; Title from title page (viewed July 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 31 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Change is the only constant; upgrades are inevitable. Believe it or not, this also applies to your database. There are many drivers for such changes, such as technology stack updates and new data center or event cloud migrations. A database migration isn’t an easy task. Preparation and execution takes time and leaves no room for mistakes. And once you start, there’s no going back. But is this the only way? Adrian Lungu and Serban Teodorescu (Adobe) explain how—inspired by the green-blue deployment technique—the Adobe Audience Manager team developed an active-passive database migration procedure that allows them to test database clusters in production, minimizing the risks without compromising the innovation. It was successfully applied twice to upgrade the entire database technology stack—but it’s never a smooth move when your databases are 200-node Cassandra clusters with hundreds of terabytes of data and downtime is not an option. The first migration was focused only on software upgrades. For the second upgrade, the team’s confidence was so high that they added a twist: a couple of more changes besides the Cassandra version—AWS instance type, operating system, disk settings, memory settings, JVM, and a few more. What could go wrong? Well. . .everything. Adrian and Serban describe the migration technique and present an extensible database client that makes all the active-passive management possible with just a configuration change. Yes, you heard it right. No code changes, just configurations. They then share a series of tales and lessons learned during the migration of over 500 Cassandra nodes. Most of the lessons aren’t Cassandra related but instead apply to hardware, drivers, operating system, or the JVM—debugging for days and searching for that metric anomaly or that log line that would give us a hint on what went wrong. Join in to see how you can avoid some of these pitfalls in your own projects. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 26 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Choreographed microservices talk to each other asynchronously, blindly broadcasting notifications into a service cloud. Those notifications are handled by whatever client services are interested. These systems eliminate many of the problems associated with orchestrated systems (which work more like synchronous function calls) and are typically much faster than orchestrated systems, but they have their own idiosyncrasies and implementation challenges. Allen Holub explores the inherent problems in orchestrated systems and then looks at how choreography can solve those problems. Allen explores three approaches to choreography: HTTP based, pub/sub messaging based, and brokerless swarming systems. He introduces appropriate messaging architectures and frameworks and looks at several practical examples. Finally, Allen looks at event storming: one of the best approaches to designing choreographed systems. You’ll leave with an understanding of both why you should be using choreography for most high-level APIs and how to design and build these systems. This session was recorded at the 2019 O'Reilly Software Architecture Conference in San Jose.
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Much of the hardest work of creating effective data products in the enterprise is not in the complexity of the algorithms applied but in effective design and integration into downstream systems. Hilary Mason (Cloudera) shares a process for repeatedly creating effective AI products, from idea through process to specific design considerations, and explains how architecture and algorithmic choices can support or hinder this process. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 24 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Analytics and AI are powerful methods for extracting insights hidden in data. However, these methods by themselves cannot convey insights. Visualization is a key requirement for explaining analytical findings, but visualizations such as graphs and charts are not always enough to explain data, especially to a nontechnical audience. This audience may need a different approach to connect with the data. Nancy Rausch (SAS Institute) shares a case study for a project that combined machine learning and art to tell a big data story. She explains how she and her team collected and prepared IoT streaming data from a solar array farm, applied an analytical model to forecast future output, and then visualized the results for general audiences using interactive art. They also used artificial intelligence and natural language processing to allow visitors to interact with the art installation. The project brought solar array technology to life in a way that was able to engage and delight visitors of all ages and backgrounds. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (60 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Innovation and competition are driving analysts and data scientists toward increasingly complex predictive modeling and machine learning algorithms. This complexity makes these models accurate, but can also make their predictions difficult to understand. When accuracy outpaces interpretability, human trust suffers, affecting business adoption, model validation efforts, and regulatory oversight. In the updated edition of this ebook, Patrick Hall and Navdeep Gill from H2O.ai introduce the idea of machine learning interpretability and examine a set of machine learning techniques, algorithms, and models to help data scientists improve the accuracy of their predictive models while maintaining a high degree of interpretability. While some industries require model transparency, such as banking, insurance, and healthcare, machine learning practitioners in almost any vertical will likely benefit from incorporating the discussed interpretable models, and debugging, explanation, and fairness approaches into their workflow. This second edition discusses new, exact model explanation techniques, and de-emphasizes the trade-off between accuracy and interpretability. This edition also includes up-to-date information on cutting-edge interpretability techniques and new figures to illustrate the concepts of trust and understanding in machine learning models. Learn how machine learning and predictive modeling are applied in practice Understand social and commercial motivations for machine learning interpretability, fairness, accountability, and transparency Get a definition of interpretability and learn about the groups leading interpretability research Examine a taxonomy for classifying and describing interpretable machine learning approaches Gain familiarity with new and more traditional interpretable modeling approaches See numerous techniques for understanding and explaining models and predictions Read about methods to debug prediction errors, sociological bias, and security vulnerabilities in predictive models Get a feel for the techniques in action with code examples
    Note: Online resource; Title from title page (viewed October 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Architects are leaders. We need to understand our business, our users, and our ecosystem. We need to effectively interact with our stakeholders, productively collaborate with design and product teams, and give direction and motivate our development teams. Achieving these goals requires much more than technical excellence. Seth Dobbs (Bounteous) shares a primer on leadership for architects, focusing on guiding principles that are easy to learn and put into practice. Principles cover both inward focus (personal mastery) and external focus (effective interactions) and include topics such as vision, problem solving, ownership, and conflict. Seth explores material he’s used to train team members ranging from developers and designers up into the executive level but focuses on core guiding principles specific to helping architects be more effective in their roles. Each principle will be presented first with a problem or anti-pattern, then the principle, and then examples of the principle in practice. This approach should be valuable whether you are new in a leadership role and looking to understand the “soft” skills required or have been leading for a while and want to formalize your thinking on leadership. This session was recorded at the 2019 O'Reilly Software Architecture Conference in San Jose.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (84 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Blockchains have many uses beyond cryptocurrencies such as Bitcoin. These shared, distributed ledgers also enable businesses to record transactions between parties in an efficient, verifiable, and permanent manner—unlike traditional methods. Using a blockchain in business can still pose numerous challenges, however. This ebook explains how developers can establish a blockchain network to handle business-to-business transactions while maintaining privacy and confidentiality. Members of IBM’s global blockchain team show you how to start using these open, distributed ledgers to add value to your business networks. Unlike simple ledgers and contracts, blockchains offer irrefutable proof that all parties involved in a transaction agree to the details—creating a source of truth that today’s conventional business-to-business systems lack. You’ll learn: How blockchains for business provide a shared, distributed ledger with smart contracts How to identify and implement the scenarios for which blockchain is most suited What developers need to know about enterprise blockchain The important design and architectural considerations when building a blockchain-based platform How chaincode encapsulates business logic to define assets and the terms of transactions How to implement a blockchain application based on a commercial paper case study What the future holds for blockchain
    Note: Online resource; Title from title page (viewed July 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (39 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: There’s a powerful new tool in the fight against malware. The US National Security Agency (NSA) recently released its reverse engineering framework, Ghidra, as free and open source software. This practical report explains how engineers can use Ghidra to analyze malware and determine its impact on vulnerable systems. Developers can also use this tool to get a detailed look at compiled programs. Information security experts Ric Messier and Matthew Berninger show you how Ghidra helps you to analyze compiled code on Linux, Windows, and macOS. You’ll be able to visually inspect a program, follow the path of execution, and analyze the code from function call to function call. The more you work with Ghidra, the more you’ll understand how effective this platform is. Get a feature overview of Ghidra, including a quick look into its origins Explore program use cases, including malware analysis, compiler comparison, and efficiency improvements Learn the advantages of running this Java-based framework in a container Perform code analysis by disassembling and graphing a program using Ghidra’s CodeBrowser tool Run Ghirdra on innocuous programs before analyzing code that may be infected
    Note: Online resource; Title from title page (viewed October 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 42 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Games are wonderful contained problem spaces, making them great places to explore AI—even if you’re not a game developer. Paris Buttfield-Addison (Secret Lab Pty. Ltd.), Mars Geldard (University of Tasmania), and Tim Nugent (lonely.coffee) teach you how to use Unity to train, explore, and manipulate intelligent agents that learn. You’ll train a quadruped to walk, then train it to explore, fetch, and manipulate the world. It’s a little bit technical, a little bit creative. Join Paris, Mars, and Tim to learn how to use game technologies such as Unity to further your understanding of machine learning fundamentals and solve problems. Topics include: How video game engines are a perfect environment to constrain a problem and train an agent How easy it is to get started, using Unity How to build up a model and use it in the engine to explore a particular idea or problem This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 37 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Much progress has been made over the past decade on process and tooling for managing large-scale, multitier cloud apps and APIs, but there is far less common knowledge on best practices for managing machine-learned models (classifiers, forecasters, etc.), especially beyond the modeling, optimization, and deployment process once these models are in production. A key mindset shift required to address these issues is understanding that model development is different than software development in fundamental ways. David Talby (Pacific AI) shares real-world case studies showing why this is true and explains what you can do about it, covering key best practices that executives, solution architects, and delivery teams must take into account when committing to successfully deliver and operate data science-intensive systems in the real world. Topics include: Concept drift (Machine-learned models begin degrading as soon as they’re deployed and must adapt to a changing environment.) Locality and limited reuse and generalization of models A/B testing challenges, which make it very hard in practice to know which model will perform better in production Semisupervised and adversarial learning scenarios, which require modeling and optimizing models only once they’re in production The impact of all of the above on product planning, staffing, and client expectation management This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Language: English
    Pages: 1 online resource (35 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Imagine a situation where your service reports as healthy and serving but you receive multiple user reports of poor availability. How are these users accessing your service? Most likely, they’re using a client application, such as a mobile phone. Traditionally, SRE has only supported systems and services running in data centers rather than code running on the client, which has impeded issue detection. This report examines the challenges of client-side reliability and provides a useful set of SRE concepts and tools you can apply to your own apps. Four site reliability engineers from Google share their experiences developing and supporting first-party native mobile applications. You’ll learn core concepts critical to engineering reliable client apps as well as phenomena unique to mobile applications and key takeaways from issues caused by or related to them, including: Designing mobile apps that are resilient to unexpected inputs Rolling out changes in a controlled, metric-driven way Monitoring apps in production by measuring critical user interactions Releasing changes using feature flags so they can be evaluated and rolled back independently Understanding and preparing for your app’s impact on servers Using practices that avoid feedback patterns between your apps and services
    Note: Online resource; Title from title page (viewed July 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (77 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: DevOps is much more than a set of practices to eliminate silos between development and operations groups. If your company’s DevOps transformation is to succeed, you need to blur the lines between business and technology domains. This report helps engineering leaders understand what drives the business and provides best practices for aligning technology with business goals to increase efficiency and improve the bottom line. Author Leon Fayer, vice president of software development at Teaching Strategies, provides methods and techniques to help your organization improve cross-departmental processes, cooperation, and visibility. Getting IT and business groups to adopt DevOps principles will go a long way toward accomplishing that goal. This report shows you how. Use practical strategies to teach stakeholders how DevOps can provide value for the business Quantify the ROI value of DevOps implementation and culture changes Determine the best ways to position technology groups to support business outcomes Improve communication efficiency to identify mistakes and optimize service delivery Understand the importance of continuous insight into business performance Build empathy and trust by encouraging people to support common goals and solve problems together
    Note: Online resource; Title from title page (viewed July 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (94 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: What are the challenges to creating, running, and supporting cloud native microservices? In this report, developer advocates from IBM explain what you need to know when building new cloud-based applications. Software developers will learn how to work with Java and several modern techniques to develop, deploy, and secure microservices in a cloud native environment. You’ll examine the key principles for microservices—such as data consistency and continuous delivery—that not only are important for a cloud application but also support the operational and deployment needs of today’s applications in general. Learn exactly what cloud native means and why open source, open communities, and open standards are critical to the future of these highly available applications. Understand why open source technologies are ideal for cloud development Work with the author’s example coffee-shop application Learn the Java runtimes and frameworks that offer the best foundation for cloud native applications Start by implementing service components that have a direct relation to your business use case Secure REST services, handle service faults, and communicate what your services do Consider the observability of your cloud-native application before writing its functionality
    Note: Online resource; Title from title page (viewed October 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (350 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: In the past few years, going cloud native has been a big advantage for many companies. But it’s a tough technique to get right, especially for enterprises with critical legacy systems. This practical hands-on guide examines effective architecture, design, and cultural patterns to help you transform your organization into a cloud native enterprise—whether you’re moving from older architectures or creating new systems from scratch. By following Wealth Grid, a fictional company, you’ll understand the challenges, dilemmas, and considerations that accompany a move to the cloud. Technical managers and architects will learn best practices for taking on a successful company-wide transformation. Cloud migration consultants Pini Reznik, Jamie Dobson, and Michelle Gienow draw patterns from the growing community of expert practitioners and enterprises that have successfully built cloud native systems. You’ll learn what works and what doesn’t when adopting cloud native—including how this transition affects not just your technology but also your organizational structure and processes. You’ll learn: What cloud native means and why enterprises are so interested in it Common barriers and pitfalls that have affected other companies (and how to avoid them) Context-specific patterns for a successful cloud native transformation How to implement a safe, evolutionary cloud native approach How companies addressed root causes and misunderstandings that hindered their progress Case studies from real-world companies that have succeeded with cloud native transformations
    Note: Online resource; Title from title page (viewed November 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 29 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Choreographed microservices talk to each other asynchronously, blindly broadcasting notifications into a service cloud. Those notifications are handled by whatever client services are interested. These systems eliminate many of the problems associated with orchestrated systems (which work more like synchronous function calls) and are typically much faster than orchestrated systems, but they have their own idiosyncrasies and implementation challenges. Allen Holub explores the inherent problems in orchestrated systems and then looks at how choreography can solve those problems. Allen explores three approaches to choreography: HTTP based, pub/sub messaging based, and brokerless swarming systems. He introduces appropriate messaging architectures and frameworks and looks at several practical examples. Finally, Allen looks at event storming: one of the best approaches to designing choreographed systems. You’ll leave with an understanding of both why you should be using choreography for most high-level APIs and how to design and build these systems. This session was recorded at the 2019 O'Reilly Software Architecture Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (412 pages)
    Edition: 5th edition
    Keywords: Electronic books ; local
    Abstract: Design a complete Voice over IP (VoIP) or traditional PBX system with Asterisk, even if you have only basic telecommunications knowledge. This bestselling guide makes it easy with a detailed roadmap that shows you how to install and configure this open source software, whether you’re upgrading your existing phone system or starting from scratch. Ideal for Linux administrators, developers, and power users, this updated fifth edition shows you how to set up VoIP-based private telephone switching systems within the enterprise. You’ll get up to speed on the features in Asterisk 16, the latest long-term support release from Digium. This book also includes new chapters on WebRTC and the Asterisk Real-time Interface (ARI). Discover how WebRTC provides a new direction for Asterisk Gain the knowledge to build a simple but complete phone system Build an interactive dialplan, using best practices for Asterisk’s advanced features Learn how ARI has emerged as the API of choice for interfacing web development languages with Asterisk
    Note: Online resource; Title from title page (viewed June 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (246 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: When you need answers about using C# 8.0, this tightly focused and practical book tells you exactly what you need to know without long intros or bloated samples. Easy to browse, C# 8.0 Pocket Reference is ideal as a quick source of information or as a guide to get you rapidly up to speed if you already know Java, C++, or an earlier C# version. All programs and code snippets are available as interactive samples in LINQPad. You can edit these samples and instantly see the results without needing to set up projects in Visual Studio. Written by the author of C# 7.0 in a Nutshell , this pocket reference covers C# 8.0 without skimping on detail, including: C# fundamentals and features new to C# 8.0 Advanced topics like operator overloading, type constraints, iterators, nullable types, operator lifting, lambda expressions, and closures LINQ: sequences, lazy execution, standard query operators, and query expressions Unsafe code and pointers, custom attributes, preprocessor directives, and XML documentation
    Note: Online resource; Title from title page (viewed November 19, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 40 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: You’ve spent hundreds of hours cleaning your data, engineering features, and training and tuning your model to pinpoint accuracy. But now it’s time to deploy your model into production. Whether you lead a team of data scientists or are one yourself, you know how time-consuming and problematic deployment can be. Language and environment incompatibilities, manual and duplicative processes, out-of-control costs, and poor communication can destroy all the work you’ve put into building models and slow your machine learning efforts. Learning common deployment architectures for machine learning in the real world and understanding how to build your model for a production environment can help you avoid pitfalls when scaling up. Diego Oppenheimer (Algorithmia) discusses common problems and solutions and shares best practices from leading organizations that have solved the deployment headache. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (495 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Work with petabyte-scale datasets while building a collaborative, agile workplace in the process. This practical book is the canonical reference to Google BigQuery, the query engine that lets you conduct interactive analysis of large datasets. BigQuery enables enterprises to efficiently store, query, ingest, and learn from their data in a convenient framework. With this book, you’ll examine how to analyze data at scale to derive insights from large datasets efficiently. Valliappa Lakshmanan, tech lead for Google Cloud Platform, and Jordan Tigani, engineering director for the BigQuery team, provide best practices for modern data warehousing within an autoscaled, serverless public cloud. Whether you want to explore parts of BigQuery you’re not familiar with or prefer to focus on specific tasks, this reference is indispensable.
    Note: Online resource; Title from title page (viewed October 30, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (45 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Kubernetes use has grown quickly—not simply for convenience or efficiency but for its extensibility and capacity to adapt to any environment. If you’re a software engineer with a working knowledge of Kubernetes, this practical report demonstrates how to extend this container orchestration system to take advantage of all its capabilities. Specifically, you’ll learn how to use work queues, reconciliation loops, controllers, and operators. Gianluca Arbezzano from InfluxData shows you why Kubernetes is much more than an end application. Extending Kubernetes with its API to implement and automate flows or to gain more visibility into your system more than justifies the system’s cost and complexity. With this report, you’ll learn the right way to use everything it has to offer. Make Kubernetes a commodity to achieve stability, security, and a simpler UX Learn why Kubernetes extensibility can help you provide a solid user experience Explore the Kubernetes API and its software development kits, including the Go SDK Create easy but powerful integration using the CRUD client or kubectl plug-ins Explore Kubernetes primitives, including shared informers, the work queue, and custom resource definitions
    Note: Online resource; Title from title page (viewed July 25, 2019)
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    Language: English
    Pages: 1 online resource (1 video file, approximately 3 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In this brief introduction to Tim O'Reilly's Expert Playlist , find out why he selected these books as great examples of how to write a technical book.
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 4 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In this brief introduction to Tim O'Reilly's Expert Playlist , find out why he selected these pieces to study how some of the most advanced companies on the planet not only use technology but build their culture to support it.
    Note: Online resource; Title from title screen (viewed August 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 34 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Quantitative finance is a rich field in finance where advanced mathematical and statistical techniques are employed by both sell-side and buy-side institutions. Techniques like time series analysis, stochastic calculus, multivariate statistics, and numerical optimization are often used by “quants” for modeling asset prices, portfolio construction and optimization, and building automated trading strategies. Chakri Cherukuri (Bloomberg LP) explains how machine learning and deep learning techniques are being used in quantitative finance. Chakri outlines use cases for machine learning in finance and dives into a few examples, involving both structured and unstructured datasets, to examine in detail how machine learning models can be used for predictive analytics. Chakri details how these models work under the hood and explores the interpretability of these models. Along the way, you’ll look at novel interactive visualizations and diagnostic plots that will help you better understand these models.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 75 hr., 47 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Why did companies like Intuit, JP Morgan Chase, MasterCard, and BuzzFeed deploy AI and what business advantages have they already reaped from those deployments? How have the toolsets recently developed at Google (BERT) and Microsoft (Project Brainwave) opened up AI as a mainstream business reality? How does IBM's AI Fairness 360 toolkit combat the very real problem of unwanted bias in AI applications? You'll find the answers to these questions and many more in this video compilation of the best talks from AI New York 2019. Containing hours of material to explore at your own pace, this video compilation provides an insider's view of the latest developments in AI. Highlights include:M/p〉 Complete video recordings of the talks delivered at AI NY 2019 by 170 of the world's top AI experts. Keynote addresses from AI's best thinkers, such as MIT's Aleksander Madry, Intuit's Desiree Gosby, Princeton University's Olga Troyanskaya, Netflix's Tony Jebara, Stanford University's Christopher Ré, Facebook's Kim Hazelwood, Carnegie Mellon University's Martial Hebert, and Primer's Sean Gourley, plus a look at Dell's "Sophia", the world’s first robot citizen. All of the Executive Briefings and detailed case studies from the exclusive AI Business Summit, including Kristian Hammond's (Northwestern Computer Science) day long tutorial offering a practical framework for bringing AI into your company; Adam Cheyer's (Samsung) look at how AI enables a totally new form of software development where humans and machines work collaboratively together; and Jennifer Fernick's (NCC Group) learned predictions of the industries that will benefit from the coming intersection of quantum computing, machine learning, and AI. Tutorials by AI's most experienced practitioners, including Gunnar Carlsson (Stanford University) on using topological data analysis to understand, build, and improve neural networks; Bruno Goncalves (JPMorgan Chase) on using recurrent neural networks for time series analysis; and Mo Patel (Independent) on how to build machine learning models in PyTorch. Sessions focused on machine learning, including Alina Matyukhina's (Canadian Institute for Cybersecurity) reveal of the methods dishonest actors use ML to mimic the coding style of software developers in open source projects; Chakri Cherukuri's (Bloomberg LP) discussion of how to apply machine learning and deep learning techniques in quantitative finance; and Cibele Montez Halasz's (Twitter) description of time...
    Note: Online resource; Title from title screen (viewed April 17, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 49 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: It turns out that domain-driven design is not just for cargo shipping. Vladik Khononov (Naxex) explains how he and his team embraced domain-driven design (DDD) (with very limited resources and a very short time to market) at Plexop, a large-scale marketing system that spans over a dozen different business domains. Join in to learn how DDD allowed the team to manage business complexities, find out strategies for defining context boundaries, explore lessons learned the hard way, and discover where they had to adapt the DDD methodology to fit the company’s needs. This session was recorded at the 2019 O'Reilly Software Architecture Conference in New York.
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (531 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: WordPress is much more than a blogging platform. As this practical guide clearly demonstrates, you can use WordPress to build web apps of any type—not mere content sites, but full-blown apps for specific tasks. If you have PHP experience with a smattering of HTML, CSS, and JavaScript, you’ll learn how to use WordPress plugins and themes to develop fast, scalable, and secure web apps, native mobile apps, web services, and even a network of multiple WordPress sites. In the book's updated second edition, the authors use examples from their recently released SchoolPress app to explain concepts and techniques throughout the book. All code examples are available on GitHub. Compare WordPress with traditional app development frameworks Use themes for views, and plugins for backend functionality Get suggestions for choosing WordPress plugins—or build your own Manage user accounts and roles, and access user data Build asynchronous behaviors in your app with jQuery Develop native apps for iOS and Android, using wrappers Incorporate PHP libraries, external APIs, and web service plugins Collect payments through ecommerce and membership plugins Use techniques to speed up and scale your WordPress app With Early Release ebooks, you get books in their earliest form—the author’s raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles.
    Note: Online resource; Title from title page (viewed December 18, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 18 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Software systems always express some form of architecture. Many times those architectures reflect the mere circumstances and microtrends prevailing at various times. But long-term success doesn’t happen by accident. When approached deliberately, software architecture and design can produce benefits for teams in a variety of ways. James Thompson (Cingo Solutions) demonstrates how to assess approaches and make decisions based on what matters to your team and your projects by answering the following guiding questions: What is software architecture? What decisions are architectural? How do you discuss software architecture? How do you document architectural decisions? How do you encourage continued learning? These questions give you a framework for thinking about how to do software architecture in a collaborative way. Software development is a collaborative effort, and software architecture should be also. Software architecture is something that every developer should be equipped and empowered to engage with—leading to a more collaborative way of developing and maintaining your software systems. This session was recorded at the 2019 O'Reilly Software Architecture Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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  • 70
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 35 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Brands, marketers, and product designers need to understand their customers. Traditionally, market research was driven by surveys and focus groups of limited scale. Today, digital signals like web browsing behavior can provide a stream of observed behavioral data that is rich with information about a user’s interests, needs, and preferences. This type of data, coupled with machine learning techniques, holds the promise of freeing market research from the constraints of self-reported customer data. In its raw state, web browsing data is both too detailed and too sparse to be comprehensible, let alone actionable. Melinda Han Williams (Dstillery) explores semantic embeddings as a novel approach for understanding observed digital consumer behavior and details how to use a semantic embedding of web browsing behavior to drive unsupervised clustering for customer segmentation. You’ll learn how Dstillery has trained a neural network on 15 billion behavioral interactions. The resulting model can be seen as a much lower dimensional embedding of the internet and, if projected into two or three dimensions, as an interactive map. This taxonomy of internet behavior can be used as the foundation for a number of applications, providing unparalleled insights into consumer behavior and needs. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (2 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Cloud computing is the practice of storing data, software, and services online so you can access and consume them remotely over the internet. This infographic describes the options and benefits of cloud computing as well as the common deployment models.
    Note: Online resource; Title from title page (viewed July 15, 2019)
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  • 72
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (69 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: While the merits of cryptocurrency continue to be debated, the underlying technology—the blockchain—can be applied in many other ways to solve problems that have plagued organizations for years. To spur adoption of blockchain for these newer use cases, many technology providers and leading businesses have begun offering cloud-based blockchain-as-a-service (BaaS) options. This report brings you up to speed on these emerging opportunities. Author Karen Kilroy helps technical business leaders, solutions architects, and innovation officers understand blockchain and evaluate options for BaaS. Through interviews with enterprise blockchain experts and practitioners, you’ll learn how this service model has evolved and what it offers. You’ll also examine the landscape of BaaS offerings, get a project started, and learn where the technology is going. You’ll learn: Why blockchain is different from a relational database or other distributed ledger technologies How blockchain is used in business applications The nuts and bolts of a blockchain network, including participants, assets, transactions, and smart contracts How to architect a typical BaaS application as a standalone multiuser application Current BaaS offerings and how to choose the one that’s right for you Five industry-changing use cases for BaaS, including international trade, identity verification, and royalties tracking Examples of how BaaS may be used in the future
    Note: Online resource; Title from title page (viewed November 25, 2019)
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  • 73
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (30 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Many modern programming languages include libraries to handle performance, multiple cores, structured data, errors or failures, and other tasks. Ballerina builds many of these tasks directly into the language. With this brief introduction, developers and software architects will learn how Ballerina can speed development and reduce failures in today’s cloud native, distributed environments. Ballerina is a general-purpose cloud native programming language that specializes in integration. On the surface, it looks like many other C-style languages, but Ballerina also contains features that incorporate current best practices for web programming, microservices, and Agile- or DevOps-oriented development. In this report, O’Reilly editor Andy Oram helps you understand what Ballerina offers and how it solves modern development problems. You’ll explore how: High-level Ballerina features make it easier to conduct network activities This language is designed around DevOps practices with an IDE-based build system Ballerina includes a module for continuous integration and testing Modules for deploying programs on Docker, Kubernetes, or AWS Lambda are included Ballerina also features compiler extensions, security, concurrency, and error checking
    Note: Online resource; Title from title page (viewed October 25, 2019)
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  • 74
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (38 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Many SRE tasks are the same across all types of software, yet individual teams often develop very different automation tools and processes and can resist standardization. Why does this diversity exist? And how can an organization prevent SRE teams from duplicating their development efforts while cutting down on their manual labor? This case study details how and why several teams at Google eventually gravitated to one tool—Sisyphus—despite its lack of managerial support, best practices, and high-quality code. Google engineer Richard Bondi examines how Sisyphus was able to proliferate across Google’s SRE teams. You’ll delve into data that demonstrates Sisyphus’s adoption success and learn how this tool overcame two significant challenges along the way. This case study offers site reliability engineers, managers, and organizational practitioners a clear example of how a tool influenced SRE behavior by adapting to SRE culture. You’ll explore ways to: Tailor tool development to the specifics of your organization's environment Design tools that are adaptable to individual SRE teams Accommodate teams and individuals who have traditionally been resistant to top-down mandates Decide when a tool is "good enough" rather than perfect
    Note: Online resource; Title from title page (viewed July 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (20778 pages)
    Edition: 1st edition
    Keywords: Audiobooks ; local
    Abstract: This audio book is for Product Managers of all levels (including the VP level) who understand that if companies want to remain innovative in today’s market, they have to adopt a culture of learning and customer-centric practices that are focused on outcomes over outputs. This audio book provides Product Managers with a practical process and a toolbox of product management principles that can be applied to any company, big or small, and will help them produce real positive results. They will learn how to overcome product development roadblocks, the secrets to communicating and collaborating within a company structure, and how to build products that benefit both the business and the customer.
    Note: Online resource; Title from title page (viewed April 15, 2019)
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  • 76
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 40 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In a large global health services company, streaming data for processing and sharing comes with its own challenges. Data science and analytics platforms need data fast, from relevant sources, to act on this data quickly and share the insights with consumers with the same speed and urgency. Join Mohammad Quraishi (Cigna) to learn why streaming data architectures are a necessity—Kafka and Hadoop are key. Mohammad outlines architectures centered around the Hadoop Platform and Kafka that were implemented to support a variety of integration and analytics requirements. Topics include: Enabling streaming to and from relational sources and files using custom frameworks that automate and speed up workflows Combining the polyglot techniques with Kafka API to support various streaming solutions Combining data driven techniques to support consumers through a simple streaming architecture and microservices How HBase, Kudu, and Kafka Streams are used to reduce latency between these microservices and frontend application APIs Enabling the consumption and sharing of data sources and results using streams Enabling Spark Structured Streaming, Flink, and Spark ML on these streams Enabling data sync between on-premises data lakes and the cloud Supporting cloud native architectures that enable machine learning in the cloud This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (263 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: TypeScript is a typed superset of JavaScript with the potential to solve many of the headaches for which JavaScript is famous. But TypeScript has a learning curve of its own, and understanding how to use it effectively can take time. This book guides you through 62 specific ways to improve your use of TypeScript. Author Dan Vanderkam, a principal software engineer at Sidewalk Labs, shows you how to apply these ideas, following the format popularized by Effective C++ and Effective Java (both from Addison-Wesley). You’ll advance from a beginning or intermediate user familiar with the basics to an advanced user who knows how to use the language well. Effective TypeScript is divided into eight chapters: Getting to Know TypeScript TypeScript’s Type System Type Inference Type Design Working with any Types Declarations and types Writing and Running Your Code Migrating to TypeScript
    Note: Online resource; Title from title page (viewed October 23, 2019)
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  • 78
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (361 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: The Digital Age is having a broad and profound impact on companies and entire industries. Rather than simply automate or embed digital technology into existing offerings, your business needs to rethink everything. In this practical book, three ThoughtWorks professionals provide a game plan to help your business through this transformation, along with technical concepts that you need to know to be an effective leader in a modern digital business. Chock-full of practical advice and case studies that show how businesses have transitioned, this book reveals lessons learned in guiding companies through digital transformation. While there’s no silver bullet available, you’ll discover effective ways to create lasting change at your organization. With this book, you’ll discover how to: Realign the business and operating architecture to focus on customer value Build a more responsive and agile organization to deal with speed and ambiguity Build next generation technology capability as a core differentiator
    Note: Online resource; Title from title page (viewed October 30, 2019)
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  • 79
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 42 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Before any analysis can begin, a data scientist needs to discover the right data sources to analyze, understand them, and determine whether they can trust them. Unfortunately, data discovery is very inefficient today. Countless hours are lost trying to find the right data to use. (The most common way still remains to ask a coworker.) Gaining trust in data requires running a bunch of queries (max timestamp, counts per day, count distincts, etc.) that waste time and add unnecessary load on the databases. There’s no clear way to know how to find folks to answer questions about the table. And worst of all, many times analysis is redone and models are rebuilt because previous work isn’t discoverable. Lyft has reduced the time it takes to discover data by 10x by building its own data portal, Amundsen. Amundsen is built on three key pillars: an augmented data graph, an intuitive user experience, and centralized metadata. Amundsen uses a graph database under the hood to store relationships between various data assets (tables, dashboards, protobuf events, etc.). What’s unique to Amundsen is that it treats people as a first-class data asset; in other words, there’s a graph node for each person in the organization that connects to other nodes (like tables, and dashboards). In addition, Amundsen runs PageRank using data from access logs to power search ranking, similar to how Google ranks web pages on the internet. Finally, Amundsen gathers metadata from various different sources (Hive, Presto, Airflow, etc.) and exposes it in one central place. The right place to store all this metadata is a work in progress. Mark Grover and Tao Feng (Lyft) offer a demo of Amundsen and lead a deep dive into its architecture, covering how it leverages centralized metadata, page rank, and a comprehensive data graph to achieve its goal. They also explore the future roadmap, unsolved problems, and its collaboration model. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 42 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Arun Kejariwal (Independent) and Ira Cohen (Anodot) share a novel two-step approach for building more reliable prediction models by integrating anomalies in them. The first step uses anomaly detection algorithms to discover anomalies in a time series in the training data. In the second, multiple prediction models, including time series models and deep networks, are trained, enriching the training data with the information about the anomalies discovered in the first step. Anomaly detection for individual time series is a necessary but insufficient step due to the fact that anomaly detection over a set of live data streams may result in anomaly fatigue, thereby limiting effective decision making. One way to address the above is to carry out anomaly detection in a multidimensional space. However, this is typically very expensive computationally and hence not suitable for live data streams. Another approach is to carry out anomaly detection on individual data streams and then leverage correlation analysis to minimize false positives, which in turn helps in surfacing actionable insights faster. They then walk you through marrying correlation analysis with anomaly detection, discuss how the topics are intertwined, and detail the challenges you may encounter based on production data. They also showcase how deep learning can be leveraged to learn nonlinear correlation, which in turn can be used to further contain the false positive rate of an anomaly detection system. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: The rise of the servant leader is due to a shift away from top-down managerial thinking. Not only are employees empowered, but a new focus on the customer means feedback has multiple pathways into an organization—and many new couriers of that information. So, what is a servant leader? This infographic describes servant leadership and how it can benefit your organization.
    Note: Online resource; Title from title page (viewed July 15, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 43 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: As microservices, data services, and serverless APIs proliferate in a cloud native world, analysts still need to report on the business as a whole. Data engineers need to collect and standardize data in an increasingly complex and diverse system. Luckily, the problem is also the solution. The way to manage data in a cloud native environment is to build cloud native data pipelines. Gwen Shapira (Confluent) discusses how data engineering requirements have changed in a cloud native world and how the solutions have changed with them. She then shares architectural patterns that are commonly used to build cloud native data infrastructure and explains how they help you build flexible, scalable, and reliable pipelines to give your business visibility on all your data. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 45 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Most software engineers come up through the ranks as coders and believe that the valuable lessons they’ve learned from their years in the trenches are an infallible guide to the future. While experience is certainly useful, the emerging field of cognitive psychology has another story to tell: the real reasons for our decisions aren’t entirely the subject of our conscious choice—or even awareness. Ian Varley (Salesforce) covers the emerging field of cognitive biases—bugs in our mental operating system—and takes a cold, hard look at how these mental blind spots defeat our attempts to build quality software in every domain. (If you’ve read books like Thinking Fast and Slow and You Are Not So Smart , you’ll be familiar with the basic idea.) While awareness of cognitive biases is a good life skill in general, it’s particularly critical if you’re in a software architect role, because your opinions set the conditions for massive amounts of work by other engineers. As such, it’s worth the time to thoroughly debug your own process for learning and making important decisions. Ian explains why the sunk cost fallacy means you’re not throwing things out fast enough; how confirmation bias can sneak into even the most data-driven decisions; how hindsight bias is obscuring the real lessons you might have learned from that failed project; how priming and fixation is shooting down your most promising inputs; and how arguing over architectural decisions is unlikely to help anybody. (See also: “Nobody ever changed their mind between Vim and Emacs.”) Most importantly, Ian shares concrete techniques you can use to check your own decision making for these unwelcome guests. We might not be capable of being perfectly rational beings, but we can be a lot less dumb. This session was recorded at the 2019 O'Reilly Software Architecture Conference in San Jose.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (250 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Despite many uncertainties in cloud computing, one truth is evident: costs will always tend to go up unless you’re actively engaged in the process. Whether you’re new to managing cloud spend or a seasoned pro, this book will clarify the often misunderstood workings of cloud billing fundamentals and provide expert strategies on creating a culture of cloud cost management in your organization. Drawing on real-world examples of successes and failures of large-scale cloud spenders, this book outlines a road map for building a culture of FinOps in your organization. Beginning with the fundamental concepts required to understand cloud billing concepts, you’ll learn how to enable an efficient and effective FinOps machine. Learn how the cloud works when it comes to financial management Set up a FinOps team and build a framework for making spend efficiency a priority Examine the anatomy of a cloud bill and learn how to manage it Get operational recipes for maximizing cloud efficiency Understand how to motivate engineering teams to take cost-saving actions Explore the FinOps lifecycle: Inform, Optimize, and Operate Learn the DNA of a highly functional cloud FinOps culture
    Note: Online resource; Title from title page (viewed December 24, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (27 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: According to a recent poll conducted by O’Reilly Media, most data scientists already know what AI technologies, such as deep learning, can do. Now they want to learn how to implement neural networks and deep learning to address their unique business objective. They’re looking for business use cases, real-world examples, and tutorials and tips for overcoming challenges with these projects. And they’re seeking a Cloud-based service so they can spin up a service in matter of minutes and only pay for what they use. With tools such as Deep Learning as a Service within IBM Watson Studio, building and deploying deep learning models in the enterprise is getting easier. This practical report provides enterprise application developers with specific use cases and steps for implementation, data scientist Federico Castanedo provides readers with a foundational understanding of deep learning and demonstrates how companies are using it in their business today. You’ll learn two approaches to implementing deep learning in your organization: build and train your own deep learning models, or leverage pre-trained models. Learn what deep learning can do in the enterprise Understand the general process of building and training neural networks in-house for deep learning projects Contrast building your own solution with using and deploying pre-built models Design deep learning models in the cloud with IBM Watson Studio and popular frameworks such as TensorFlow, Caffe, PyTorch and Keras
    Note: Online resource; Title from title page (viewed October 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 45 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Quantitative finance is a rich field in finance where advanced mathematical and statistical techniques are employed by both sell-side and buy-side institutions. Techniques like time series analysis, stochastic calculus, multivariate statistics, and numerical optimization are often used by "quants” for modeling asset prices, portfolio construction and optimization, and building automated trading strategies. Chakri Cherukuri (Bloomberg LP) demonstrates how to apply machine learning techniques in quantitative finance, covering use cases involving both structured and alternative datasets. The focus of the talk will be on promoting reproducible research (through Jupyter notebooks and interactive plots) and interpretable models. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (46 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Cloud deployments have not only changed the way companies run mission critical databases; they’ve also transformed the roles of many people in production. With this practical report, database and system administrators, IT managers, and DevOps engineers will learn the ins and outs of running databases in the cloud. You’ll explore the types of databases available, the difference between standard database services versus cloud native databases, and key considerations when planning the migration of on-premises databases to the cloud. Authors Wendy Neu, Vlad Vlasceanu, Andy Oram, and Sam Alapati explain how high-performing, highly available cloud environments free DBAs to focus on their core competencies, such as designing databases and optimizing applications that rely on them, while cloud providers handle the organization’s routine infrastructure needs. With this report, you’ll learn: The pros and cons of options in the cloud, such as managed, self-managed, and cloud native How the cloud transforms a DBA’s role, including the new tasks a DBA needs to learn when cloud vendors assume traditional administrative tasks Steps required for migrating your databases to the cloud, such as planning, data transfer, and optimization
    Note: Online resource; Title from title page (viewed November 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (50 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Companies and their customers today often don’t focus on the same things. While a restaurant may work hard to create an exciting new menu item, diners care more about courtesy. A bank will spend thousands promoting trust while customers struggle to access their website. This report explains how service design can help your organization innovate to deliver great experiences, not just great products, by understanding your customers' needs. Service design experts Adam Lawrence, Marc Stickdorn, Markus Hormeß, and Jakob Schneider explain that service design is a mindset, a process, a toolset, and a cross-disciplinary language. You’ll learn how cross-functional teams can create and orchestrate great customer or employee experiences that satisfy the requirements of the business, the user, and other stakeholders. This report explores how: Service design applies to physical and digital products as well as services Today’s informed customers have created a new challenge for businesses Service design is similar to design thinking and compatible with Agile and Lean Designers can promote low-risk progress through iterative prototyping Lightweight, iterative research can keep teams from solving the wrong problem This approach offers a common language for cross-silo collaboration
    Note: Online resource; Title from title page (viewed August 25, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 58 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Ethical lapses aren’t just embarrassing and expensive—they can put your organization at serious risk in a number of ways and damage its reputation and bottom line. If you collect any kind of data, you’re more vulnerable to ethical errors than you may realize. From acquisition and model-building to algorithms, it’s critical to view all aspects of data science through an ethical lens and implement best practices to ensure accuracy. We need only look to some very public failures as proof. Learn about three cases when data ethics mistakes cost companies both money and trust—and how your business can avoid their mistakes. Recorded on January 29, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Learning from Failure , you’ll discover the lessons learned from failures both large and small. You’ll discover how successful companies have addressed setbacks, missteps, and challenges and how you can grow from their examples.
    Note: Online resource; Title from title screen (viewed August 27, 2019)
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 57 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: LaunchDarkly’s Heidi Waterhouse shares some of the biggest challenges in feature management. In a perfect world, we’d develop tidy, discrete features that are easy to manage. But in reality, we’re often struggling with a complicated snarl of features that are difficult to test and deploy. Heidi explains how you can use feature management design to build modular, testable, resilient systems. Recorded on April 23, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Innovation , you’ll discover what successful companies have in common and how you can follow their lead with small practical steps to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed September 17, 2019)
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  • 91
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 0 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Startups seem to come out of nowhere, disrupting their markets and leaving traditional organizations to ask themselves how they too can adopt cloud-centric models and approaches. But just how realistic is this? Today’s enterprises are sometimes criticized for legacy thinking, but they also have to bear the burden of infrastructure, supply chains, security, governance frameworks, and customer drivers that can’t be changed at the flick of the switch. Here's the good news: enterprise concerns and cloud native principles may be better aligned than you think. Flexible infrastructure is becoming a staple of modern data centers. Microservices models align with software architecture best practices, while Agile innovation approaches such as DevOps are maturing in governance. At the same time, cybersecurity and risk management is an area of traditional strength, and operational principles used in the enterprise are as important as ever. Find out how businesses can adopt cloud native principles without throwing away what it means to be an enterprise. Recorded on May 2, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Cloud , you’ll learn about the complex, ever-evolving world of the cloud. You’ll discover how successful companies have adopted and embraced this massive network of shared information and how you can follow their lead to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed September 17, 2019)
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  • 92
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (331 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With this practical book, architects, CTOs, and CIOs will learn a set of patterns for the practice of architecture, including analysis, documentation, and communication. Author Eben Hewitt shows you how to create holistic and thoughtful technology plans, communicate them clearly, lead people toward the vision, and become a great architect or Chief Architect. This book covers each key aspect of architecture comprehensively, including how to incorporate business architecture, information architecture, data architecture, application (software) architecture together to have the best chance for the system’s success. Get a practical set of proven architecture practices focused on shipping great products using architecture Learn how architecture works effectively with development teams, management, and product management teams through the value chain Find updated special coverage on machine learning architecture Get usable templates to start incorporating into your teams immediately Incorporate business architecture, information architecture, data architecture, and application (software) architecture together
    Note: Online resource; Title from title page (viewed October 2, 2019)
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  • 93
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (484 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Native Application Development will provide engineers with professionally developed and curated recipes for the 20 of the most common tasks that represent functionality seen in modern native iOS and Android applications. The selected tasks will provide a cross-reference for each platform–a modern Rosetta Stone, of sorts. A developer can look up an easily translatable set of instructions for completing a routine bit of functionality in both platforms in a way that follows best practices. Following that, we'll provide step-by-step direction to create a fully-functional application using modern practices and designs that will utilize those tasks, one in each platform. The development of the apps will be laid out side-by-side, so that the friction usually involved in switching between platforms while developing is greatly reduced. By the end of the book, the reader will have developed both an iOS app and an Android with exactly the same core features, as well as some additional features that are relevant and unique to each app’s operating system. This book will provide a blueprint for software engineers to create an app that will reach 99.9% of the smartphone market, while functioning as a Rosetta stone in multi-platform development. The reality of modern application development is that most developers will need to have some reference across platforms at some point, if not as a regular requirement.
    Note: Online resource; Title from title page (viewed November 13, 2019)
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  • 94
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (293 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: If you’re like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems. Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Analyze, explore, transform, and visualize data in Apache Spark with R Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows Perform analysis and modeling across many machines using distributed computing techniques Use large-scale data from multiple sources and different formats with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions
    Note: Online resource; Title from title page (viewed October 11, 2019)
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  • 95
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (38 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With more and more companies moving on-prem applications to the cloud, software and cloud solution architects alike are busy investigating ways to improve load balancing, performance, security, and high availability for workloads. This practical report describes Microsoft Azure’s load balancing options and explains how NGINX can contribute to a comprehensive solution. Cloud solution architect Arlan Nugara takes you through the steps necessary to design a practical solution for your network. Software developers and technical managers will learn how these technologies have a direct impact on application development and architecture. While the examples are specific to Azure, these load balancing concepts and implementations also apply to cloud providers such as AWS, Google Cloud Platform, DigitalOcean, and IBM Cloud. Understand load balancing—what it is and why it’s important Explore load balancing in Azure, including the traffic manager and application gateway Learn how NGINX Plus on Azure lets you create an ideal end-to-end application platform Walk through three load balancing options with Azure and NGINX Plus Explore security choices including NGINX management, NGINX Web Application Firewall, and Azure Firewall integration
    Note: Online resource; Title from title page (viewed July 25, 2019)
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  • 96
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (203 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Until recently, learning CoreDNS required reading the code or combing through the skimpy documentation on the website. No longer. With this practical book, developers and operators working with Docker or Linux containers will learn how to use this standard DNS server with Kubernetes. John Belamaric, senior staff software engineer at Google, and Cricket Liu, chief DNS architect at Infoblox, show you how to configure CoreDNS using real-world configuration examples to achieve specific purposes. You’ll learn the basics of DNS, including how it functions as a location broker in container environments and how it ties into Kubernetes. Dive into DNS theory: the DNS namespace, domain names, domains, and zones Learn how to configure your CoreDNS server Manage and serve basic and advanced zone data with CoreDNS Configure CoreDNS service discovery with etcd and Kubernetes Learn one of the most common use cases for CoreDNS: the integration with Kubernetes Manipulate queries and responses as they flow through the plug-in chain Monitor and troubleshoot the availability and performance of your DNS service Build custom versions of CoreDNS and write your own plug-ins
    Note: Online resource; Title from title page (viewed September 9, 2019)
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  • 97
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (391 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Serverless computing greatly simplifies software development. Your team can focus solely on your application while the cloud provider manages the servers you need. This practical guide shows you step-by-step how to build and deploy complex applications in a flexible multicloud, multilanguage environment using Apache OpenWhisk. You’ll learn how this platform enables you to pursue a vendor-independent approach using preconfigured containers, microservices, and Kubernetes as your cloud operating system. Michele Sciabarrà demonstrates how to build a serverless application using classical design patterns and the programming language or languages that best fit your task. You’ll start by building a simple serverless application hands-on before diving into the more complex aspects of the OpenWhisk platform. Examine how OpenWhisk’s serverless architecture works, including the use of packages, actions, sequences, triggers, rules, and feeds Learn how OpenWhisk compares to existing architectures, such as Java Enterprise Edition Manipulate OpenWhisk features using the command-line interface or a JavaScript API Design applications using common Gang of Four design patterns Use architectural design patterns such as model-view-controller to combine several OpenWhisk actions Learn how to test and debug your code in a serverless environment
    Note: Online resource; Title from title page (viewed July 9, 2019)
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  • 98
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (64 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Many large organizations have accumulated dozens of disconnected data sources to serve different lines of business over the years. These applications might be useful to one area of the enterprise, but they’re usually inaccessible to other data consumers in the organization. In this short report, five data industry thought leaders explore DataOps—the automated, process-oriented methodology for making clean, reliable data available to teams throughout your company. Andy Palmer, Michael Stonebraker, Nik Bates-Haus, Liam Cleary, and Mark Marinelli from Tamr use real-world examples to explain how DataOps works. DataOps is as much about changing people’s relationship to data as it is about technology, infrastructure, and process. This report provides an organizational approach to implementing this discipline in your company—including various behavioral, process, and technology changes. Through individual essays, you’ll learn how to: Move toward scalable data unification (Michael Stonebraker) Understand DataOps as a discipline (Nik Bates-Haus) Explore the key principles of a DataOps ecosystem (Andy Palmer) Learn the key components of a DataOps ecosystem (Andy Palmer) Build a DataOps toolkit (Liam Cleary) Build a team and prepare for future trends (Mark Marinelli)
    Note: Online resource; Title from title page (viewed June 25, 2019)
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  • 99
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (327 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN
    Note: Online resource; Title from title page (viewed June 28, 2019)
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  • 100
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    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (35 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Despite the size or scale of your production environment, your organization can gain significant value by adopting DevOps practices. Yet most organizations today still deploy application code and packages manually. To facilitate your adoption of DevOps-style practices, this hands-on guide shows you how to automate your IT operations using HashiCorp Terraform and VMware. DevOps is as much a people and process change as it is a technology change. Terraform and VMware provide the automation infrastructure, so you can focus on acquiring and adapting DevOps skills and processes. Eric Wright, technology evangelist at Turbonomic, shows architects and administrators how to build and operate VMware vSphere virtual machines and infrastructure using the Terraform CLI. With this report, you will: Learn how to codify virtual infrastructure step-by-step Understand how DevOps processes apply to VMware infrastructure Easily build VMware virtual machines and applications as Terraform resources Perform lifecycle management and immutable concepts using Terraform and VMware
    Note: Online resource; Title from title page (viewed September 25, 2019)
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