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Keras Reinforcement Learning Projects

You're reading from Keras Reinforcement Learning Projects 9 projects exploring popular reinforcement learning techniques to build self-learning agents

Product type Paperback

Published in Sep 2018

Publisher Packt

ISBN-13 9781789342093

Length 288 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Reinforcement Learning

Author (1):

Giuseppe Ciaburro

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Table of Contents (13) Chapters

Preface

1. Overview of Keras Reinforcement Learning FREE CHAPTER

2. Simulating Random Walks

3. Optimal Portfolio Selection

4. Forecasting Stock Market Prices

5. Delivery Vehicle Routing Application

6. Continuous Balancing of a Rotating Mechanical System

7. Dynamic Modeling of a Segway as an Inverted Pendulum System

8. Robot Control System Using Deep Reinforcement Learning

9. Handwritten Digit Recognizer

10. Playing the Board Game Go

11. What's Next?

12. Other Books You May Enjoy

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Preface

This book brings human-level performance into your applications using the algorithms and techniques of reinforcement learning coupled with Keras, the fast experimental library. Some of the projects that are covered are a delivery vehicle routing application, forecasting stock market prices, a robot control system, a optimal portfolio selection, and the dynamic modeling of a Segway. Throughout this book, you will get your hands dirty with the most popular algorithms, such as the Markov Decision Process, the Monte Carlo method, and Q-learning, so that you can be equipped with complex statistics to get better results.

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Authors (1)

Giuseppe Ciaburro

Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).

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