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Preview: New: All Things O'Reilly

New: All Things O'Reilly



A resource for the developer who looks to O'Reilly as an independent source of information for open and emerging technologies



Last Build Date: Fri, 23 Jun 2017 04:21:20 PDT

Copyright: Copyright O'Reilly Media, Inc.
 



#Ebook Deal/Day: Building Microservices with ASP.NET Core - $25.49 (Save 50%) Use code DEAL

Fri, 23 Jun 2017 04:31:20 PDT

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Get "Building Microservices with ASP.NET Core" today using code DEAL and save 50%!

This sale ends at 2:00 AM 2017-06-26 (PDT, GMT-8:00).




#Ebook Deal/Day: Text Mining with R - $16.99 (Save 50%) Use code DEAL

Thu, 22 Jun 2017 04:28:02 PDT

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Get "Text Mining with R" today using code DEAL and save 50%!

This sale ends at 2:00 AM 2017-06-23 (PDT, GMT-8:00).




Incident Management for Operations

Wed, 21 Jun 2017 04:33:53 PDT

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Are you satisfied with the way your company responds to IT incidents? How prepared is your response team to handle critical, time-sensitive events such as service disruptions and security breaches? IT professionals looking for effective response models have successfully adopted the Incident Management System (IMS) used by firefighters throughout the US. This practical book shows you how to apply the same response methodology to your own IT operation. You’ll learn how IMS best practices for leading people and managing time apply directly to IT incidents where the stakes are high and outcomes are uncertain.




#Ebook Deal/Day: Deep Learning: Practical Neural Networks with Java - $33.99 (Save 50%) Use code DEAL

Tue, 20 Jun 2017 04:29:48 PDT

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Get "Deep Learning: Practical Neural Networks with Java" today using code DEAL and save 50%!

This sale ends at 2:00 AM 2017-06-21 (PDT, GMT-8:00).




How and Where to Reach Desktop Developers

Mon, 19 Jun 2017 14:34:52 PDT

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This report provides insight into how and where desktop developers get their sustenance.




Zero Trust Networks

Mon, 19 Jun 2017 14:35:19 PDT

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The perimeter defenses guarding your network perhaps are not as secure as you think. Hosts behind the firewall have no defenses of their own, so when a host in the "trusted" zone is breached, access to your data center is not far behind. That’s an all-too-familiar scenario today. With this practical book, you’ll learn the principles behind zero trust architecture, along with details necessary to implement it.




Building Microservices with ASP.NET Core

Mon, 19 Jun 2017 04:36:53 PDT

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Pick up best patterns and practices for building microservices with ASP.NET Core—the new, improved, cross-platform reincarnation of ASP.NET. With this practical guide, you’ll not only learn how to integrate many factors of cloud native application development into your own projects, you’ll also learn disciplines and strategies for building horizontally scalable services.




#Ebook Deal/Day: Mastering Django: Core - $19.99 (Save 50%) Use code DEAL

Mon, 19 Jun 2017 04:33:53 PDT

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Get "Mastering Django: Core" today using code DEAL and save 50%!

This sale ends at 2:00 AM 2017-06-20 (PDT, GMT-8:00).




Principles of Data Wrangling

Fri, 16 Jun 2017 04:40:14 PDT

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A key task that any aspiring data-driven organization needs to learn is data wrangling, the process of converting raw data into something truly useful. This book provides business analysts with an overview of various data wrangling techniques and tools, and puts the practice of data wrangling into context by asking, "what are you trying to do and why?" The authors walk you through the wrangling process by exploring several considerations you need to take into account as you begin to work with data, including time, granularity, scope, and structure.

One of the first lessons you’ll learn in this special preview edition of the book is how data wrangling is a different process than data analysis. In fact, roughly 50-80% of an analyst’s time is spent wrangling data to the point where any kind of analysis is possible. Wrangling involves a set of tasks that enable you to:

  • Understand what data is available
  • Choose which data to use and at what level of detail
  • Meaningfully combine multiple sources of data
  • Decide how to distill the results to a size and shape that can drive downstream analysis

This book provides you with a shared language and a comprehensive understanding of data wrangling, with an emphasis on recent and quickly growing agile analytic processes in data-driven organizations. You’ll come to appreciate the importance—and the satisfaction—of wrangling data the right way.

About the authors:

Tye Rattenbury is a lead data scientist at Trifacta. He holds a Ph.D. in Computer Science from UC Berkeley. Prior to Trifacta, he was a Data Scientist at Facebook and the Director of Data Science Strategy at R/GA.

Joe Hellerstein is Trifacta’s Chief Strategy Officer and a Professor of Computer Science at Berkeley. His career in research and industry has focused on data-centric systems and the way they drive computing.

Sean Kandel is Trifacta’s Chief Technical Officer. He completed his Ph.D. at Stanford University, where his research focused on user interfaces for database systems. At Stanford, Sean led development of new tools for data transformation and discovery, such as Data Wrangler.




How and Where to Reach Cloud Developers

Thu, 15 Jun 2017 04:40:57 PDT

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This report provides insight into how and where cloud developers get their sustenance.




Agile Data Science 2.0

Thu, 15 Jun 2017 04:41:57 PDT

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Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.




Administering a SQL Database Infrastructure - Exam 70-764 Certification Training

Thu, 15 Jun 2017 04:42:57 PDT

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Microsoft's SQL Server platform is one of the top three relational database products in the world's enterprise marketplace, which means that those with SQL Server skills are in high demand everywhere. This course is designed for those who want to become a SQL Server administrator.

The course prepares you to take Microsoft exam 70-764, the first of two tests you must pass in order to earn the Microsoft Certified Solutions Associate (MCSA): SQL 2016 Database Administration certification. Passing the 70-764 exam indicates to the world that you have what it takes to administer the SQL database infrastructure.

  • Learn about the topics that will be covered on Microsoft exam 70-764
  • Get closer to earning the MCSA SQL 2016 Database Administration certification
  • Understand the structure and implementation of SQL Server security
  • Discover how encryption is utilized and implemented in SQL Server 2016
  • Learn how to manage indexes on the SQL Server platform
  • See how data backups and restorations happen on the SQL Server 2016 platform
  • Survey the tools used to monitor and tune SQL Server performance
Mark Long is a long term contributor to O'Reilly Media having authored more than a dozen book and video titles including CompTIA Security+ SY0-401 (2014 Objectives), Windows Presentation Foundation Basics, Learning Windows PowerShell, and Securing Windows Networks. Mark holds many certifications including Microsoft's MCSE, MCDBA, and MCT; and as the head of his own consulting company, he solves IT issues for numerous Fortune 500 companies.



Deep Learning: Practical Neural Networks with Java

Thu, 15 Jun 2017 04:43:57 PDT

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Build and run intelligent applications by leveraging key Java machine learning libraries

About This Book

  • Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries.
  • Explore a broad variety of data processing, machine learning, and natural language processing through diagrams, source code, and real-world applications
  • This step-by-step guide will help you solve real-world problems and links neural network theory to their application

Who This Book Is For

This course is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life.

What You Will Learn

  • Get a practical deep dive into machine learning and deep learning algorithms
  • Explore neural networks using some of the most popular Deep Learning frameworks
  • Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms
  • Apply machine learning to fraud, anomaly, and outlier detection
  • Experiment with deep learning concepts, algorithms, and the toolbox for deep learning
  • Select and split data sets into training, test, and validation, and explore validation strategies
  • Apply the code generated in practical examples, including weather forecasting and pattern recognition

In Detail

Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognitionStarting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. This course helps you solve challenging problems in image processing, speech recognition, language modeling. You will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text. You will also work with examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work.

The course provides you with highly practical content explaining deep learning with Java, from the following Packt books:

  1. Java Deep Learning Essentials
  2. Machine Learning in Java
  3. Neural Network Programming with Java, Second Edition

Style and approach

This course aims to create a smooth learning path that will teach you how to effectively use deep learning with Java with other de facto components to get the most out of it. Through this comprehensive course, you'll learn the basics of predictive modelling and progress to solve real-world problems and links neural network theory to their application




Microsoft Dynamics 365 Extensions Cookbook

Thu, 15 Jun 2017 04:44:57 PDT

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More than 80 recipes to help you leverage the various extensibility features available for Microsoft Dynamics and solve problems easily

About This Book

  • Customize, configure, and extend the vanilla features of Dynamics 365 to deliver bespoke CRM solutions fit for any organization
  • Implement business logic using point-and-click configuration, plugins, and client-side scripts with MS Dynamics 365
  • Built a DevOps pipeline as well as Integrate Dynamics 365 with Azure and other platforms

Who This Book Is For

This book is for developers, administrators, consultants, and power users who want to learn about best practices when extending Dynamics 365 for enterprises. You are expected to have a basic understand of the Dynamics CRM/365 platform.

What You Will Learn

  • Customize, configure, and extend Microsoft Dynamics 365
  • Create business process automation
  • Develop client-side extensions to add features to the Dynamics 365 user interface
  • Set up a security model to securely manage data with Dynamics 365
  • Develop and deploy clean code plugins to implement a wide range of custom behaviors
  • Use third-party applications, tools, and patterns to integrate Dynamics 365 with other platforms
  • Integrate with Azure, Java, SSIS, PowerBI, and Octopus Deploy
  • Build an end-to-end DevOps pipeline for Dynamics 365

In Detail

Microsoft Dynamics 365 is a powerful tool. It has many unique features that empower organisations to bridge common business challenges and technology pitfalls that would usually hinder the adoption of a CRM solution. This book sets out to enable you to harness the power of Dynamics 365 and cater to your unique circumstances.

We start this book with a no-code configuration chapter and explain the schema, fields, and forms modeling techniques. We then move on to server-side and client-side custom code extensions. Next, you will see how best to integrate Dynamics 365 in a DevOps pipeline to package and deploy your extensions to the various SDLC environments. This book also covers modern libraries and integration patterns that can be used with Dynamics 365 (Angular, 3 tiers, and many others). Finally, we end by highlighting some of the powerful extensions available.

Throughout we explain a range of design patterns and techniques that can be used to enhance your code quality; the aim is that you will learn to write enterprise-scale quality code.

Style and approach

This book takes a recipe-based approach, delivering practical examples and use cases so that you can identify the best possible approach to extend your Dynamics 365 deployment and tackle your specific business problems.




Implementing and Testing Applications using Functional JavaScript

Thu, 15 Jun 2017 04:45:57 PDT

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See how to build and test your application using functional programming

About This Video

  • Configure and structure a web application written in the functional style
  • Learn the ins and outs of unit testing a functional web application with popular automated testing libraries
  • Optimize the performance of your applications using functional programming
  • Understand functional programming by learning about concepts in a simple and practical way

In Detail

You will get an in-depth overview of how to handle asynchronous code with promises, generator functions, and the ES2017 async-await construct. These tools will help you set up communication with a server via an API later, when implementing a web application.

Lazy evaluation will allow you to optimize performance of retrieving a collection of data, where you may need to process and retrieve just a fraction of the available elements. This powerful technique will not only allow you to write performant code, but it also makes it possible for you to handle infinite sequences.

We will also implement a web application together, demonstrating the practical usage of most of the features you learned in this course, and in the previous volume of this course, Deep Dive into Functional JavaScript. You will see higher order functions, currying, partial evaluation, recursion, ES6, asynchronous code with promises and ES2017 async-await, and many more language construct and functional programming ideas in practice. While we anchor these techniques into your mind with the repeated practical usage, you will also learn about techniques to write maintainable software: test driven development, top-down design, and bottom-up design. We will use Mocha and ChaiJs to write unit tests for the functional part of the application




Capture One Pro 10

Thu, 15 Jun 2017 04:46:57 PDT

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Historically, Capture One Pro software has been regarded primarily as an amazing RAW file converter for high-end cameras. With its newest release, Capture One Pro 10 goes well beyond its storied RAW conversions to become one of the most powerful image-processing applications on the market, addressing the imaging workflow from capture to print. Version 10 has also been optimized to support many of the most popular cameras being used today.

With an abundance of new features and the promise of producing vastly superior images, photographers of all skill levels are giving Capture One Pro a try. Of course, along with expanded functionality and improved performance, the software has become a challenge to learn efficiently on one’s own. Users need a helping hand in order to get up to speed and make sure they are taking full advantage of this powerful software.

In Capture One Pro 10: Mastering RAW Development, Image Processing, and Asset Management, photographer Sascha Erni teaches readers everything they need to know in order to quickly get up and running with Capture One Pro. He also dives deeply into its extensive feature list to allow users to fully explore the capabilities of the software. Whether you’re moving to Capture One Pro from Aperture or Lightroom, or just beginning to learn image-editing with Capture One Pro 10, this book will teach you how to get amazing results while avoiding frustration and wasted time along the way.

Topics include:

    • RAW conversion
    • Asset management
    • Converting to black-and-white
    • Eliminating lens errors
    • Tethered shooting/live view
    • Film grain simulation
    • Working with layers
    • HDR imaging
    • Much, much more



Data Lake for Enterprises

Thu, 15 Jun 2017 04:47:57 PDT

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A practical guide to implementing your enterprise data lake using Lambda Architecture as the base

About This Book

  • Build a full-fledged data lake for your organization with popular big data technologies using the Lambda architecture as the base
  • Delve into the big data technologies required to meet modern day business strategies
  • A highly practical guide to implementing enterprise data lakes with lots of examples and real-world use-cases

Who This Book Is For

Java developers and architects who would like to implement a data lake for their enterprise will find this book useful. If you want to get hands-on experience with the Lambda Architecture and big data technologies by implementing a practical solution using these technologies, this book will also help you.

What You Will Learn

  • Build an enterprise-level data lake using the relevant big data technologies
  • Understand the core of the Lambda architecture and how to apply it in an enterprise
  • Learn the technical details around Sqoop and its functionalities
  • Integrate Kafka with Hadoop components to acquire enterprise data
  • Use flume with streaming technologies for stream-based processing
  • Understand stream- based processing with reference to Apache Spark Streaming
  • Incorporate Hadoop components and know the advantages they provide for enterprise data lakes
  • Build fast, streaming, and high-performance applications using ElasticSearch
  • Make your data ingestion process consistent across various data formats with configurability
  • Process your data to derive intelligence using machine learning algorithms

In Detail

The term "Data Lake" has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects ? data lake and lambda architecture?together.

This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient.

By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake.

Style and approach

The book takes a pragmatic approach, showing ways to leverage big data technologies and lambda architecture to build an enterprise-level data lake.




Apache Spark 2.x Cookbook

Thu, 15 Jun 2017 04:48:57 PDT

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Over 70 recipes to help you use Apache Spark as your single big data computing platform and master its libraries

About This Book

  • This book contains recipes on how to use Apache Spark as a unified compute engine
  • Cover how to connect various source systems to Apache Spark
  • Covers various parts of machine learning including supervised/unsupervised learning & recommendation engines

Who This Book Is For

This book is for data engineers, data scientists, and those who want to implement Spark for real-time data processing. Anyone who is using Spark (or is planning to) will benefit from this book. The book assumes you have a basic knowledge of Scala as a programming language.

What You Will Learn

  • Install and configure Apache Spark with various cluster managers & on AWS
  • Set up a development environment for Apache Spark including Databricks Cloud notebook
  • Find out how to operate on data in Spark with schemas
  • Get to grips with real-time streaming analytics using Spark Streaming & Structured Streaming
  • Master supervised learning and unsupervised learning using MLlib
  • Build a recommendation engine using MLlib
  • Graph processing using GraphX and GraphFrames libraries
  • Develop a set of common applications or project types, and solutions that solve complex big data problems

In Detail

While Apache Spark 1.x gained a lot of traction and adoption in the early years, Spark 2.x delivers notable improvements in the areas of API, schema awareness, Performance, Structured Streaming, and simplifying building blocks to build better, faster, smarter, and more accessible big data applications. This book uncovers all these features in the form of structured recipes to analyze and mature large and complex sets of data.

Starting with installing and configuring Apache Spark with various cluster managers, you will learn to set up development environments. Further on, you will be introduced to working with RDDs, DataFrames and Datasets to operate on schema aware data, and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will also work through recipes on machine learning, including supervised learning, unsupervised learning & recommendation engines in Spark.

Last but not least, the final few chapters delve deeper into the concepts of graph processing using GraphX, securing your implementations, cluster optimization, and troubleshooting.

Style and approach

This book is packed with intuitive recipes supported with line-by-line explanations to help you understand Spark 2.x's real-time processing capabilities and deploy scalable big data solutions. This is a valuable resource for data scientists and those working on large-scale data projects.




Building Bots with Microsoft Bot Framework

Thu, 15 Jun 2017 04:49:57 PDT

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Build intelligent and smart conversational interfaces using Microsoft Bot Framework

About This Book

  • Develop various real-world intelligent bots from scratch using Microsoft Bot Framework
  • Integrate your bots with most popular conversation platforms such as Skype, Slack, and Facebook Messenger
  • Flaunt your bot building skills in your organization by thoroughly understanding and implementing the bot development concepts such as messages (rich text and pictures), dialogs, and third-party authentication and calling

Who This Book Is For

This book is for developers who are keen on building powerful services with great and interactive bot interface. Experience with C# is needed.

What You Will Learn

  • Set up a development environment and install all the required software to get started programming a bot
  • Publish a bot to Slack, Skype, and the Facebook Messenger platform
  • Develop a fully functional weather bot that communicates the current weather in a given city
  • Help your bot identify the intent of a text with the help of LUIS in order to make decisions
  • Integrate an API into your bot development
  • Build an IVR solution
  • Explore the concept of MicroServices and see how MicroServices can be used in bot development
  • Develop an IoT project, deploy it, and connect it to a bot

In Detail

Bots help users to use the language as a UI and interact with the applications from any platform. This book teaches you how to develop real-world bots using Microsoft Bot Framework.

The book starts with setting up the Microsoft Bot Framework development environment and emulator, and moves on to building the first bot using Connector and Builder SDK. Explore how to register, connect, test, and publish your bot to the Slack, Skype, and Facebook Messenger platforms.

Throughout this book, you will build different types of bots from simple to complex, such as a weather bot, a natural speech and intent processing bot, an Interactive Voice Response (IVR) bot for a bank, a facial expression recognition bot, and more from scratch.

These bots were designed and developed to teach you concepts such as text detection, implementing LUIS dialogs, Cortana Intelligence Services, third-party authentication, Rich Text format, Bot State Service, and microServices so you can practice working with the standard development tools such as Visual Studio, Bot Emulator, and Azure.

Style and approach

This step-by-step guide takes a learn-while-doing approach, delivering the practical knowledge and experience you need to design and build real-world Bots. The concepts come to you on an as-needed basis while developing a bot so you increase your programming knowledge and experience at the same time.




Learning Spark Streaming

Thu, 15 Jun 2017 04:50:01 PDT

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To build analytics tools that provide faster insights, knowing how to process data in real time is a must, and moving from batch processing to stream processing is absolutely required. Fortunately, the Spark in-memory framework/platform for processing data has added an extension devoted to fault-tolerant stream processing: Spark Streaming.

If you're familiar with Apache Spark and want to learn how to implement it for streaming jobs, this practical book is a must.




Natural Language Processing with PyTorch

Thu, 15 Jun 2017 04:51:01 PDT

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Natural language processing (NLP) provides unbounded opportunities for solving interesting problems in artificial intelligence, especially with the availability of flexible deep learning frameworks. With this practical book, developers and data scientists will learn how to implement recently discovered NLP techniques with the open source software library TensorFlow. If you have some background in machine learning, this book will help you explore the intersection of NLP and practical aspects of deep learning.




#Ebook Deal/Day: Agile Data Science 2.0 - $19.49 (Save 50%) Use code DEAL

Thu, 15 Jun 2017 04:48:32 PDT

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Get "Agile Data Science 2.0" today using code DEAL and save 50%!

This sale ends at 2:00 AM 2017-06-16 (PDT, GMT-8:00).




#Ebook Deal/Day: Python High Performance - $15.99 (Save 50%) Use code DEAL

Wed, 14 Jun 2017 04:49:16 PDT

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Get "Python High Performance" today using code DEAL and save 50%!

This sale ends at 2:00 AM 2017-06-15 (PDT, GMT-8:00).




Data Science with Java

Mon, 12 Jun 2017 20:54:24 PDT

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Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today’s data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java.




DevOps with OpenShift

Sun, 11 Jun 2017 04:54:26 PDT

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For many organizations, a big part of DevOps’ appeal is software automation using infrastructure-as-code techniques. This book presents developers, architects, and infra-ops engineers with a more practical option. You’ll learn how a container-centric approach from OpenShift, Red Hat’s cloud-based PaaS, can help your team deliver quality software through a self-service view of IT infrastructure.

Three OpenShift experts at Red Hat explain how to configure Docker application containers and the Kubernetes cluster manager with OpenShift’s developer- and operational-centric tools. Discover how this infrastructure-agnostic container management platform can help companies navigate the murky area where infrastructure-as-code ends and application automation begins.

  • Get an application-centric view of automation—and understand why it’s important
  • Learn patterns and practical examples for managing continuous deployments such as rolling, A/B, blue-green, and canary
  • Implement continuous integration pipelines with OpenShift’s Jenkins capability
  • Explore mechanisms for separating and managing configuration from static runtime software
  • Learn how to use and customize OpenShift’s source-to-image capability
  • Delve into management and operational considerations when working with OpenShift-based application workloads
  • Install a self-contained local version of the OpenShift environment on your computer