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Hands-On Data Science and Python Machine Learning

You're reading from   Hands-On Data Science and Python Machine Learning Perform data mining and machine learning efficiently using Python and Spark

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787280748
Length 420 pages
Edition 1st Edition
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Author (1):
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Frank Kane Frank Kane
Author Profile Icon Frank Kane
Frank Kane
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Table of Contents (11) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Statistics and Probability Refresher, and Python Practice 3. Matplotlib and Advanced Probability Concepts 4. Predictive Models 5. Machine Learning with Python 6. Recommender Systems 7. More Data Mining and Machine Learning Techniques 8. Dealing with Real-World Data 9. Apache Spark - Machine Learning on Big Data 10. Testing and Experimental Design

Reinforcement learning

Our next topic's a fun one: reinforcement learning. We can actually use this idea with an example of Pac-Man. We can actually create a little intelligent Pac-Man agent that can play the game Pac-Man really well on its own. You'll be surprised how simple the technique is for building up the smarts behind this intelligent Pac-Man. Let's take a look!

So, the idea behind reinforcement learning is that you have some sort of agent, in this case Pac-Man, that explores some sort of space, and in our example that space will be the maze that Pac-Man is in. As it goes, it learns the value of different state changes within different conditions.

For example, in the preceding image, the state of Pac-Man might be defined by the fact that it has a ghost to the South, and a wall to the West, and empty spaces to the North and East, and that might define the...

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