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Deep Learning for Time Series Cookbook

You're reading from   Deep Learning for Time Series Cookbook Use PyTorch and Python recipes for forecasting, classification, and anomaly detection

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781805129233
Length 274 pages
Edition 1st Edition
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Authors (2):
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Luís Roque Luís Roque
Author Profile Icon Luís Roque
Luís Roque
Vitor Cerqueira Vitor Cerqueira
Author Profile Icon Vitor Cerqueira
Vitor Cerqueira
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Toc

Table of Contents (12) Chapters Close

Preface 1. Chapter 1: Getting Started with Time Series 2. Chapter 2: Getting Started with PyTorch FREE CHAPTER 3. Chapter 3: Univariate Time Series Forecasting 4. Chapter 4: Forecasting with PyTorch Lightning 5. Chapter 5: Global Forecasting Models 6. Chapter 6: Advanced Deep Learning Architectures for Time Series Forecasting 7. Chapter 7: Probabilistic Time Series Forecasting 8. Chapter 8: Deep Learning for Time Series Classification 9. Chapter 9: Deep Learning for Time Series Anomaly Detection 10. Index 11. Other Books You May Enjoy

Installing PyTorch

To start with PyTorch, we need to install it first. As of the time of writing, PyTorch supports Linux, macOS, and Windows platforms. Here, we will guide you through the installation process on these operating systems.

Getting ready

PyTorch is usually installed via pip or Anaconda. We recommend creating a new Python environment before installing the library, especially if you will be working on multiple Python projects on your system. This is to prevent any conflicts between different versions of Python libraries that different projects may require.

How to do it…

Let’s see how to install PyTorch. We’ll describe how to do this using either pip or Anaconda. We’ll also provide some information about how to use a CUDA environment.

If you’re using pip, Python’s package manager, you can install PyTorch by running the following command in your terminal:

pip install torch

With the Anaconda Python distribution,...

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Deep Learning for Time Series Cookbook
Published in: Mar 2024
Publisher: Packt
ISBN-13: 9781805129233
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