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Artificial Intelligence with Python

You're reading from   Artificial Intelligence with Python A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781786464392
Length 446 pages
Edition 1st Edition
Languages
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Author (1):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Introduction to Artificial Intelligence FREE CHAPTER 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

Chapter 15. Reinforcement Learning

In this chapter, we are going to learn about reinforcement learning. We will discuss the premise of reinforcement learning. We will talk about the differences between reinforcement learning and supervised learning. We will go through some real world examples of reinforcement learning and see how it manifests itself in various forms. We will learn about the building blocks of reinforcement learning and the various concepts involved. We will then create an environment in python to see how it works in practice. We will then use these concepts to build a learning agent.

By the end of this chapter, you will know:

  • Understanding the premise
  • Reinforcement learning vs. supervised learning
  • Real world examples of reinforcement learning
  • Building blocks of reinforcement learning
  • Creating an environment
  • Building a learning agent
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