Book Image

Artificial Intelligence with Python - Second Edition

By : Prateek Joshi
Book Image

Artificial Intelligence with Python - Second Edition

By: Prateek Joshi

Overview of this book

Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques.
Table of Contents (26 chapters)
24
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25
Index

Creating Intelligent Agents with Reinforcement Learning

In this chapter, we are going to learn about reinforcement learning (RL). We will discuss the premise of RL. We will talk about the differences between RL and supervised learning. We will go through some real-world examples of RL and see how it manifests itself in various forms. We will learn about the building blocks of RL 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.

In this chapter, we will cover the following topics:

  • Understanding what it means to learn
  • Reinforcement learning versus supervised learning
  • Real-world examples of RL
  • Building blocks of RL
  • Creating an environment
  • Building a learning agent

Before we move into RL itself, let's first think about what it actually means to learn; after all, it will help us to understand it before we go about...