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Hands-On Deep Learning for Games

You're reading from   Hands-On Deep Learning for Games Leverage the power of neural networks and reinforcement learning to build intelligent games

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781788994071
Length 392 pages
Edition 1st Edition
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Author (1):
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Micheal Lanham Micheal Lanham
Author Profile Icon Micheal Lanham
Micheal Lanham
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Table of Contents (18) Chapters Close

Preface 1. Section 1: The Basics FREE CHAPTER
2. Deep Learning for Games 3. Convolutional and Recurrent Networks 4. GAN for Games 5. Building a Deep Learning Gaming Chatbot 6. Section 2: Deep Reinforcement Learning
7. Introducing DRL 8. Unity ML-Agents 9. Agent and the Environment 10. Understanding PPO 11. Rewards and Reinforcement Learning 12. Imitation and Transfer Learning 13. Building Multi-Agent Environments 14. Section 3: Building Games
15. Debugging/Testing a Game with DRL 16. Obstacle Tower Challenge and Beyond 17. Other Books You May Enjoy

Section 1: The Basics

This section of the book covers the basic concepts of neural networks and deep learning. We'll be looking at everything from the simplest autoencoder, generative adversarial networks (GANs), and convolutional and recurrent neural networks, all the way to building a working real-world chatbot. This section will give you the basic foundations for building your neural network and deep learning knowledge.

We will include the following chapters in this section:

  • Chapter 1, Deep Learning for Games
  • Chapter 2, Convolutional and Recurrent Networks
  • Chapter 3, GAN for Games
  • Chapter 4, Building a Deep Learning Gaming Chatbot
You have been reading a chapter from
Hands-On Deep Learning for Games
Published in: Mar 2019
Publisher: Packt
ISBN-13: 9781788994071
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