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Refactoring, 2nd Edition
Refactoring, 2nd Edition

For more than twenty years, experienced programmers worldwide have relied on Martin Fowler's Refactoring to improve the design of existing code and to enhance software maintainability, as well as to make existing code easier to understand. This eagerly awaited new edition has been fully updated to reflect crucial changes in the programming landscape. Refactoring, Second Edition, features an updated catalog of refactorings and includes JavaScript code examples, as well as new functional examples that demonstrate refactoring without classes. Like the original, this edition explains what refactoring is; why you should refactor; how to recognize code that needs refactoring; and how to actually do it successfully, no matter what language you use. Understand the process and general principles of refactoring; Quickly apply useful refactorings to make a program easier to comprehend and change; Recognize “bad smells” in code that signal opportunities to refactor; Explore the refact ...
Programming Skills for Data Science
Programming Skills for Data Science

Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience. Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you've uncovered. Step by step, you'll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales. Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything's focused on real-worl ...
Google Daydream VR Cookbook
Google Daydream VR Cookbook

Google's new ARCore and Daydream VR platforms enable you to deliver advanced augmented and virtual reality games and apps on a wide spectrum of modern Android devices. Now for the first time, there's a comprehensive deep dive into both ARCore and Daydream for every Android developer and designer. Multi-award-winning AR/VR developer Sam Keene takes a hands-on approach, leading you through all aspects of the ARCore and Daydream frameworks and SDKs, with step-by-step tutorials and advice for building pro-quality AR/VR games and apps. Keene presents his material as a cookbook of recipes to get you up and running with VR/AR development as fast and as painlessly as possible. The recipes in most chapters start by assembling the essential building blocks, which are pieced together to create something larger. You are then free to take these building blocks and turn them into your own creation. Keene also provides an extensive library of downloadable, up-to-the-minute ARCore and Daydream c ...
Internet of Things Programming Projects
Internet of Things Programming Projects

The Internet of Things (IOT) has managed to attract the attention of researchers and tech enthusiasts, since it powerfully combines classical networks with instruments and devices. In Internet of Things Programming Projects, we unleash the power of Raspberry Pi and Python to create engaging projects. In the first part of the book, you'll be introduced to the Raspberry Pi, learn how to set it up, and then jump right into Python programming. Then, you'll dive into real-world computing by creating a "Hello World" app using flash LEDs. As you make your way through the chapters, you'll go back to an age when analog needle meters ruled the world of data display. You'll learn to retrieve weather data from a web service and display it on an analog needle meter, and build a home security system using the Raspberry Pi. The next project has a modern twist, where we employ the Raspberry Pi to send a signal to a web service that will send you a text when someone is at the door. In the final p ...
Machine Learning with AWS
Machine Learning with AWS

Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are highly scalable. From natural language processing (NLP) applications, such as language translation and understanding news articles and other text sources, to creating chatbots with both voice and text interfaces, you will learn all that there is to know about using AWS to your advantage. You will also understand how to process huge numbers of images fast and create machine learning models. By the end of this book, you will have developed the skills you need to efficiently use AWS in your machine learning and artificial intelligence projects. ...
Learn Android Studio 3 with Kotlin
Learn Android Studio 3 with Kotlin

Build Android apps using the popular and efficient Android Studio 3 suite of tools, an integrated development environment (IDE) with which Android developers can now use the Kotlin programming language. With this book, you'll learn the latest and most productive tools in the Android tools ecosystem, ensuring quick Android app development and minimal effort on your part. Along the way, you'll use Android Studio to develop apps tier by tier through practical examples. These examples cover core Android topics such as Activities, Intents, BroadcastReceivers, Services and AsyncTask. Then, you'll learn how to publish your apps and sell them online and in the Google Play store. Use Android Studio 3 to quickly and confidently build your first Android apps; Build an Android user interface using activities and layouts, event handling, images, menus and the action bar; Incorporate new elements including fragments; Learn how data is persisted; Use Kotlin to build apps. ...
Practical Web Development with Haskell
Practical Web Development with Haskell

Learn how to advance your skill level of Haskell, and use this language for practical web development. This book uses a direct, no nonsense approach, so you no longer need to spend extra time reading the documentation, blog posts, and forums to understand how to use Haskell - all that knowledge is provided in one coherent resource. You'll start by reviewing how multiple facets of web development are done in Haskell, such as routing, building HTMLs, interacting with databases, caches, and queues, etc. You'll then move on to using notable libraries, such as "scotty" for routings, "digestive-functor" for input validation, and "postgresql-simple" for interacting with databases. In the later chapters, you'll learn how all of these libraries can be used together by working on a fully functioning project deployed on Heroku. Set up a productive Haskell development environment; Review basic tasks that are encountered when building web applications; Explore how to interact with externa ...
Designing Scalable JavaScript Applications
Designing Scalable JavaScript Applications

If you've ever written a non-trivial JavaScript application, you know that creating a code base that's easy to maintain and scales well over time is no small feat. The complexity only grows as the project becomes larger. While it's impossible to plan for every change that could possibly happen over the life of a project, you can help future-proof your front-end architecture by designing software that's pliable and easily extended. Well-designed, extensible architecture can help reduce development and maintenance costs, as bug fixes, enhancements, and new technologies can be incorporated more easily. Designing Scalable JavaScript Applications helps you start thinking about which tools and frameworks you'll use and which design patterns you'll implement. This book brings together excerpts from four different Manning titles selected by Emmit Scott, the author of SPA Design and Architecture. These chapters are great starting points for understanding how to build better JavaScript applic ...
Exploring .NET Core with Microservices, ASP.NET Core, and Entity Framework Core
Exploring .NET Core with Microservices, ASP.NET Core, and Entity Framework Core

Windows developers have always enjoyed the productivity boost you get with the .NET platform, tools like Entity Framework and ASP.NET, and the amazingly-powerful C# language. Now, .NET Core extends those same benefits to Linux-based systems, offering a true cross-platform solution for enterprise application development. The .NET Core tools, including Entity Framework Core and ASP.NET Core, are lightweight and modular, and they offer similar performance to native Linux and JVM-based frameworks without requiring you to learn a new toolset or rebuild your applications. In a world where platform lock-in is an unpardonable sin, .NET Core offers a perfect pathway to the cloud-based, distributed environments that rule the day. Exploring .NET Core with Microservices, ASP.NET Core, and Entity Framework Core is a collection of five hand-picked chapters introducing you to the art of applying modern development practices and patterns to your .NET Core projects. In it, you'll get a quick overvie ...
Exploring Data with Python
Exploring Data with Python

Python has become a required skill for data science, and it's easy to see why. It's powerful, easy to learn, and includes the libraries like Pandas, Numpy, and Scikit that help you slice, scrub, munge, and wrangle your data. Even with a great language and fantastic tools though, there's plenty to learn! Exploring Data with Python is a collection of chapters from three Manning books, hand-picked by Naomi Ceder, the chair of the Python Software Foundation. This free eBook starts building your foundation in data science processes with practical Python tips and techniques for working and aspiring data scientists. In it, you'll get a clear introduction to the data science process. Then, you'll practice using Python for processing, cleaning, and exploring interesting datasets. Finally, you'll get a practical demonstration of modelling and prediction with classification and regression. When you finish, you'll have a good overview of Python in data science and a well-lit path to continue yo ...
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