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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

Stock Volatility Forecasting Using Long Short-Term Memory

Human beings have always tried to predict the future. Forecasting has been, therefore, one of the most studied techniques over time. Forecasts cover several fields—weather forecasts, economic and political events, sports results, and more. Since we try to predict so many different events, there are a variety of ways in which predictions can be developed.

A time series is a sequence of observations ordered with respect to time (for example, monthly turnover, the daily prices of shares, the weekly interest rate, the annual profits, and so on). The purpose of the analysis of time series consists of the study of the past evolution of the phenomenon with respect to time, in order to predict the future trend of the phenomenon. The forecast is obtained by hypothesizing that such behavioral regularities will repeat in the...

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