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Machine Learning Solutions

You're reading from   Machine Learning Solutions Expert techniques to tackle complex machine learning problems using Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788390040
Length 566 pages
Edition 1st Edition
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Table of Contents (19) Chapters Close

Machine Learning Solutions
Foreword
Contributors
Preface
1. Credit Risk Modeling 2. Stock Market Price Prediction FREE CHAPTER 3. Customer Analytics 4. Recommendation Systems for E-Commerce 5. Sentiment Analysis 6. Job Recommendation Engine 7. Text Summarization 8. Developing Chatbots 9. Building a Real-Time Object Recognition App 10. Face Recognition and Face Emotion Recognition 11. Building Gaming Bot List of Cheat Sheets Strategy for Wining Hackathons Index

Introducing the problem statement


We know we are trying to develop a gaming bot: a program that can play simple Atari games. If we provide enough time and computation resources, then it can outperform humans who are experts at playing certain games. I will list down some famous Atari games so that you can see which types of games I'm talking about. You must have played one of these games for sure. Some of the famous Atari games are Casino, Space Invaders, Pac-man, Space War, Pong (ping-pong), and so on. In short, the problem statement that we are trying to solve is how can we build a bot that can learn to play Atari games?

In this chapter, we will be using already built-in gaming environments using gym and dqn libraries. So, we don't need to create a gaming visual environment and we can focus on the approach of making the best possible gaming bot. First, we need to set up the coding environment.

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