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Keras 2.x Projects

You're reading from   Keras 2.x Projects 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789536645
Length 394 pages
Edition 1st Edition
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Author (1):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Keras FREE CHAPTER 2. Modeling Real Estate Using Regression Analysis 3. Heart Disease Classification with Neural Networks 4. Concrete Quality Prediction Using Deep Neural Networks 5. Fashion Article Recognition Using Convolutional Neural Networks 6. Movie Reviews Sentiment Analysis Using Recurrent Neural Networks 7. Stock Volatility Forecasting Using Long Short-Term Memory 8. Reconstruction of Handwritten Digit Images Using Autoencoders 9. Robot Control System Using Deep Reinforcement Learning 10. Reuters Newswire Topics Classifier in Keras 11. What is Next? 12. Other Books You May Enjoy

Implementing an LSTM to forecast stock volatility

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 is clearly linked to the opportunity to get rich through good forecasting by 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 look at how the LSTM model 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 included...

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