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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

Building the Space Invaders gaming bot


We are going to build a gaming bot that can play Space Invaders. Most of you may have played this game or at least heard of it. If you haven't played it or you can't remember it at this moment, then take a look at the following screenshot:

Figure 11.12: Snippet of the Space Invaders game

Hopefully you remember the game now and how it was played. First, we will look at the concepts that we will be using to build this version of the gaming bot. Let's begin!

Understanding the key concepts

In this version of the gaming bot, we will be using the deep Q-network and training our bot. So before implementing this algorithm, we need to understand the concepts. Take a look at the following concepts:

  • Understanding a deep Q-network (DQN)

  • Understanding Experience Replay

Understanding a deep Q-network (DQN)

The deep Q-network algorithm is basically a combination of two concepts. It uses the Q-learning logic for a deep neural network. That is the reason why it is called a...

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