Use Visual Studio Code to write and debug code quickly and efficiently on any platform, for any device, using any programming language, and on the operating system of your choice.
Visual Studio Code is an open source and cross-platform development tool that focuses on code editing across a variety of development...
Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.
Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom language processing platform for...
Learning PowerShell is a custom-built, handcrafted, painstakingly curated book designed to get you from total PowerShell newbie to confident PowerShell user in as little as four weeks. This book assumes no prior knowledge, perfect for non-developers and Gui addicts who recognize that PowerShell is the future but need a good bit of handholding...
This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...
Based on the author’s course at NYU, Linear Algebra and Probability for Computer Science Applicationsgives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the...
Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python...
Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction.
Key Features
Get up and running with the Jupyter ecosystem and some example datasets
