English | 2017 | ISBN: 178646439X | 437 pages | True (PDF,EPUB,MOB)+ Code | 102.67 MB

Publisher's Note: This edition from 2017 is outdated and not compatible with TensorFlow 2.

x or any of the most recent updates to Python libraries. A new edition completely updated and revised for 2020 with seven additional chapters that cover RNNs, AI and big data, fundamental use cases, chatbots, and more, is now available.

Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you

Key Features
Step into the amazing world of intelligent apps using this comprehensive guide
Enter the world of Artificial Intelligence, explore it, and create your own applications
Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no
Who This Book Is For
This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python bners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks.

What you will learn
Realize different classification and regression techniques
Understand the concept of clustering and how to use it to automatically snt data
See how to build an intelligent recommender system
Understand logic programming and how to use it
Build automatic speech recognition systems
Understand the basics of heuristic search and genetic programming
Develop games using Artificial Intelligence

Book Description
Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps which intelligently interact with the world around you, building intelligent recommender systems, automatic speech recognition systems and more.

Starting with AI basics you'll move on to learn how to develop building blocks using data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. This practical book covers a range of topics including predictive analytics and deep learning.



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