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Keras 2.x Projects

You're reading from  Keras 2.x Projects

Product type Book
Published in Dec 2018
Publisher Packt
ISBN-13 9781789536645
Pages 394 pages
Edition 1st Edition
Languages
Author (1):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro
Toc

Table of Contents (13) Chapters close

Preface 1. Getting Started with Keras 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

Time series models

In the previous section, Time series analysis, we explored the basics behind time series. To perform correct predictions of future events based on what happened in the past, it is necessary to construct an appropriate numerical simulation model.

Choosing an appropriate model is extremely important as it reflects the underlying structure of the series. In practice, two types of models are available: linear or nonlinear. These can be selected based on whether the current value of the series is a linear or nonlinear function of past observations.

The following are the most widely used models for forecasting time series data:

  • AR (autoregressive)
  • MA (moving average)
  • ARMA (autoregressive moving average)
  • ARIMA (autoregressive integrated moving average)

Autoregressive...

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