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Artificial Intelligence with Python Cookbook

You're reading from   Artificial Intelligence with Python Cookbook Proven recipes for applying AI algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6

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Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781789133967
Length 468 pages
Edition 1st Edition
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Authors (2):
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Ritesh Kumar Ritesh Kumar
Author Profile Icon Ritesh Kumar
Ritesh Kumar
Ben Auffarth Ben Auffarth
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Ben Auffarth
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Artificial Intelligence in Python 2. Advanced Topics in Supervised Machine Learning FREE CHAPTER 3. Patterns, Outliers, and Recommendations 4. Probabilistic Modeling 5. Heuristic Search Techniques and Logical Inference 6. Deep Reinforcement Learning 7. Advanced Image Applications 8. Working with Moving Images 9. Deep Learning in Audio and Speech 10. Natural Language Processing 11. Artificial Intelligence in Production 12. Other Books You May Enjoy

Playing blackjack

One of the benchmarks in reinforcement learning is gaming. Many different environments related to gaming have been designed by researchers or aficionados. A few of the milestones in gaming have been mentioned in Chapter 1, Getting Started with Artificial Intelligence in Python. The highlights for many would certainly be beating the human champions in both chess and Go—chess champion Garry Kasparov in 1997 and Go champion Lee Sedol in 2016—and reaching super-human performance in Atari games in 2015.

In this recipe, we get started with one of the simplest game environments: blackjack. Blackjack has an interesting property that it has in common with the real world: indeterminism.

Blackjack is a card game where, in its simplest form, you play against a card dealer. You have a deck of cards in front of you, and you can hit, which means you get one more card, or stick, where the dealer gets to draw cards. In order to win, you want to get as close as possible...

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