Head.First.Android.Development.2nd.Edition.2017.8.pdf

If you have an idea for a killer Android app, this fully revised and updated edition will help you build your first working application in a jiffy. You’ll learn hands-on how to structure your app, design flexible and interactive interfaces, run services in the background, make your app work on various smartphones and tablets, and much more. It’s like having an experienced Android developer sitting right next to you! All you need to get started is some Java know-how.

TensorFlow.Machine.Learning.Cookbook.2017.2.pdf

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You’ll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow. This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.

Thoughtful.Machine.Learning.with.Python.2017.1.pdf

Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book features tests with Python’s Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you’re a software engineer or business analyst interested in data science, this book will help you:

Test-Driven.Development.with.Python.2nd.Edition.2017.8.pdf

By taking you through the development of a real web application from beginning to end, the second edition of this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You’ll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. The result? Clean code that works. In the process, you’ll learn the basics of Django, Selenium, Git, jQuery, and Mock, along with current web development techniques. If you’re ready to take your Python skills to the next level, this book—updated for Python 3.6—clearly demonstrates how TDD encourages simple designs and inspires confidence.

VSCodeSetup-x64-1.15.1.exe

visual studio code x64 v1.15.1

RxJS.in.Action.2017.7.pdf

RxJS in Action is your guide to building a reactive web UI using RxJS. You’ll begin with an intro to stream-based programming as you explore the power of RxJS through practical examples. With the core concepts in hand, you’ll tackle production techniques like error handling, unit testing, and interacting with frameworks like React and Redux. And because RxJS builds on ideas from the world of functional programming, you’ll even pick up some key FP concepts along the way.

Streaming.Data.2017.5.pdf

Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you’ll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you’ll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details.

CoreOS.in.Action.2017.5.pdf

CoreOS in Action is a clear tutorial for deploying container-based systems on CoreOS Container Linux. Inside, you’ll follow along with examples that teach you to set up CoreOS on both private and cloud systems, and to practice common sense monitoring and upgrade techniques with real code. You’ll also explore important container-aware application designs, including microservices, web, and Big Data examples with real-world use cases to put your learning into perspective.

Deep.Learning.2017.8.pdf

Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J.

Swift.Data.Structure.and.Algorithms.2016.11.pdf

Apple’s Swift language has expressive features that are familiar to those working with modern functional languages, but also provides backward support for Objective-C and Apple’s legacy frameworks. These features are attracting many new developers to start creating applications for OS X and iOS using Swift. Designing an application to scale while processing large amounts of data or provide fast and efficient searching can be complex, especially running on mobile devices with limited memory and bandwidth. Learning about best practices and knowing how to select the best data structure and algorithm in Swift is crucial to the success of your application and will help ensure your application is a success. That’s what this book will teach you. Starting at the beginning, this book will cover the basic data structures and Swift types, and introduce asymptotic analysis. You’ll learn about the standard library collections and bridging between Swift and Objective-C collections. You will see how to implement advanced data structures, sort algorithms, work with trees, advanced searching methods, use graphs, and performance and algorithm efficiency. You’ll also see how to choose the perfect algorithm for your problem.