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

About This Book

• 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 time

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 beginners, 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 segment 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
• Learn how reinforcement learning works
• Discover how to build intelligent applications centered on images, text, and time series data
• See how to use deep learning algorithms and build applications based on it

In Detail

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.

Table of Contents

1. Introduction to Artificial Intelligence
2. Classification and Regression Using Supervised Learning
3. Predictive Analytics with Ensemble Learning
4. Detecting Patterns with Unsupervised Learning
5. Building Recommender Systems
6. Logic Programming
7. Heuristic Search Techniques
8. Genetic Algorithms
9. Building Games with Artificial Intelligence
10. Natural Language Processing
11. Probabilistic Reasoning for Sequential Data
12. Building A Speech Recognizer
13. Object Detection and Tracking
14. Artificial Neural Networks
15. Reinforcement Learning
16. Deep Learning with Convolutional Neural Networks

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