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...
Understand the big picture of the software development process. We use software every day – operating systems, applications, document editing programs, home banking – but have you ever wondered who creates software and how it’s created? This book guides you through the entire process, from conception to the finished...
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...
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...
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.
Discover how C's efficiency makes it a popular choice in a wide variety of applications and operating systems with special applicability to wearables, game programming, system level programming, embedded device/firmware programming and in Arduino and related electronics hobbies in this condensed code and syntax guide. This book...
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
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...
This book was written to provide resource materials for teachers to use in their introductory or intermediate statistics class. The chapter content is ordered along the lines of many popular statistics books so it should be easy to supplement the content and exercises with class lecture materials.
Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms.
Key Features
Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and...
Develop Intelligent Bots using Microsoft Bot framework (C# and Node.js), Visual Studio Enterprise & Code, Microsoft
Azure and Cognitive Services. This book shows you how to develop great Bots, publish to Azure and register with Bot portal so that customers can
connect and communicate using famous...
