If you’re familiar with JavaScript, this hands-on guide will quickly get you up to speed on the Angular framework for building high-performance web-based desktop, mobile, and single-page applications. Initially dubbed Angular 2, this version is a complete rewrite from the same team that built the initial version of AngularJS....

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural...

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or...

Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve...

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

Learn how to take full advantage of Apache Kafka, the distributed, publish-subscribe queue for handling real-time data feeds. With this comprehensive book, you’ll understand how Kafka works and how it’s designed. Authors Neha Narkhede, Gwen Shapira, and Todd Palino show you how to deploy production Kafka clusters; secure,...

• Your ultimate resource for getting up and running with Python numerical computations
• Explore numerical computing and mathematical libraries using Python 3.x code with SciPy and NumPy modules
• A hands-on guide to implementing mathematics with Python, with complete...

Do you want to build web pages but have no prior experience? This friendly guide is the perfect place to start. You’ll begin at square one, learning how the web and web pages work, and then steadily build from there. By the end of the book, you’ll have the skills to create a simple site with multicolumn pages that adapt...

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects...

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....

If your JavaScript is a mess, frameworks can only do so much to help. No matter what framework, "compiles-to-JS" language, or library you use, bugs and performance concerns will always be an issue if the underlying quality of your JavaScript is poor. With this hands-on guide, you’ll learn how test and refactor your...