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The Reinforcement Learning Workshop

You're reading from  The Reinforcement Learning Workshop

Product type Book
Published in Aug 2020
Publisher Packt
ISBN-13 9781800200456
Pages 822 pages
Edition 1st Edition
Languages
Authors (9):
Alessandro Palmas Alessandro Palmas
Profile icon Alessandro Palmas
Emanuele Ghelfi Emanuele Ghelfi
Profile icon Emanuele Ghelfi
Dr. Alexandra Galina Petre Dr. Alexandra Galina Petre
Profile icon Dr. Alexandra Galina Petre
Mayur Kulkarni Mayur Kulkarni
Profile icon Mayur Kulkarni
Anand N.S. Anand N.S.
Profile icon Anand N.S.
Quan Nguyen Quan Nguyen
Profile icon Quan Nguyen
Aritra Sen Aritra Sen
Profile icon Aritra Sen
Anthony So Anthony So
Profile icon Anthony So
Saikat Basak Saikat Basak
Profile icon Saikat Basak
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Toc

Table of Contents (14) Chapters close

Preface
1. Introduction to Reinforcement Learning 2. Markov Decision Processes and Bellman Equations 3. Deep Learning in Practice with TensorFlow 2 4. Getting Started with OpenAI and TensorFlow for Reinforcement Learning 5. Dynamic Programming 6. Monte Carlo Methods 7. Temporal Difference Learning 8. The Multi-Armed Bandit Problem 9. What Is Deep Q-Learning? 10. Playing an Atari Game with Deep Recurrent Q-Networks 11. Policy-Based Methods for Reinforcement Learning 12. Evolutionary Strategies for RL Appendix

Simple Classification Using TensorFlow

This section will help you understand and solve a typical supervised learning problem that falls under the category conventionally named classification.

Classification tasks, in their simplest generic form, aim to associate one category, among a predefined set, with instances. An intuitive example of a classification task that's often used for introductory courses is classifying the images of domestic pets in the correct category they belong to, such as "cat" or "dog." Classification plays a fundamental role in many everyday activities and can easily be encountered in different contexts. The previous example is a specific case of classification called image classification, and many similar applications can be found in this category.

However, classification extends beyond images. The following are some examples:

  • Customer classification for video recommendation systems (answering the question, "In which...
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