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Neural Networks with Keras Cookbook

You're reading from   Neural Networks with Keras Cookbook Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789346640
Length 568 pages
Edition 1st Edition
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Authors (2):
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V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Srinivas Pradeep Srinivas Pradeep
Author Profile Icon Srinivas Pradeep
Srinivas Pradeep
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Toc

Table of Contents (18) Chapters Close

Preface 1. Building a Feedforward Neural Network 2. Building a Deep Feedforward Neural Network FREE CHAPTER 3. Applications of Deep Feedforward Neural Networks 4. Building a Deep Convolutional Neural Network 5. Transfer Learning 6. Detecting and Localizing Objects in Images 7. Image Analysis Applications in Self-Driving Cars 8. Image Generation 9. Encoding Inputs 10. Text Analysis Using Word Vectors 11. Building a Recurrent Neural Network 12. Applications of a Many-to-One Architecture RNN 13. Sequence-to-Sequence Learning 14. End-to-End Learning 15. Audio Analysis 16. Reinforcement Learning 17. Other Books You May Enjoy

Deep Q-learning to play Space Invaders game

In the previous section, we used Deep Q-learning to play the Cart-Pole game. In this section, we will leverage Deep Q-learning to play Space Invaders, which is a more complex environment than Cart-Pole.

A sample screenshot of the Space Invaders game looks as follows:

source: https://gym.openai.com/envs/SpaceInvaders-v0/

The objective of this exercise is to maximize the score obtained in a single game.

Getting ready

The strategy that we'll adopt to build an agent that is able to maximize the score is as follows:

  • Initialize the environment of the Space Invaders-Atari2600 game.
  • Preprocess the image frame:
    • Remove pixels that do not necessarily impact the action prediction
      • For...
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