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Keras Reinforcement Learning Projects

You're reading from Keras Reinforcement Learning Projects

Product type Book

Published in Sep 2018

Publisher Packt

ISBN-13 9781789342093

Pages 288 pages

Edition 1st Edition

Languages

Concepts

Reinforcement Learning

Author (1):

Giuseppe Ciaburro

Table of Contents (13) Chapters

Preface

1. Overview of Keras Reinforcement Learning

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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Amazon stock price prediction using Python

The stock market forecast has always been a very popular topic: this is because stock market trends involve a truly impressive turnover. The interest that this topic arouses in public opinion is clearly linked to the opportunity to get rich through good forecasts of a stock market title. A positive difference between the purchased stock price and that of the sold stock price entails a gain on the part of the investor. But, as we know, the performance of the stock market depends on multiple factors. In this section, we'll see how Monte Carlo methods can be applied to predict the future stock price of a very popular company: I refer to Amazon, the US e-commerce company, based in Seattle, Washington, which is the largest internet company in the world.

Amazon has been listed on Wall Street since 1997 with the AMZN symbol; its title is...

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Authors (1)

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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