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Deep Learning for Time Series Cookbook

You're reading from  Deep Learning for Time Series Cookbook

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781805129233
Pages 274 pages
Edition 1st Edition
Languages
Authors (2):
Vitor Cerqueira Vitor Cerqueira
Profile icon Vitor Cerqueira
Luís Roque Luís Roque
Profile icon Luís Roque
View More author details

Table of Contents (12) Chapters

Preface Chapter 1: Getting Started with Time Series Chapter 2: Getting Started with PyTorch Chapter 3: Univariate Time Series Forecasting Chapter 4: Forecasting with PyTorch Lightning Chapter 5: Global Forecasting Models Chapter 6: Advanced Deep Learning Architectures for Time Series Forecasting Chapter 7: Probabilistic Time Series Forecasting Chapter 8: Deep Learning for Time Series Classification Chapter 9: Deep Learning for Time Series Anomaly Detection Index Other Books You May Enjoy

Technical requirements

This chapter requires the following Python libraries:

  • numpy (1.23.5)
  • pandas (1.5.3)
  • scikit-learn (1.2.1)
  • sktime (0.24.0)
  • torch (2.0.1)
  • pytorch-forecasting (1.0.0)
  • pytorch-lightning (2.1.0)
  • gluonts (0.13.5)
  • neuralforecast (1.6.0)

You can install these libraries in one go using pip:

pip install -U pandas numpy scikit-learn sktime torch pytorch-forecasting pytorch-lightning gluonts neuralforecast

The code for this chapter can be found at the following GitHub URL: https://github.com/PacktPublishing/Deep-Learning-for-Time-Series-Data-Cookbook.

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