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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

Tackling TSC problems with sktime

In this recipe, we explore an alternative approach to PyTorch for TSC problems, which is sktime. sktime is a Python library devoted to time series modeling, which includes several neural network models for TSC.

Getting ready

You can install sktime using pip. You’ll also need the keras-self-attention library, which includes self-attention methods necessary for running some of the methods in sktime:

pip install 'sktime[dl]'
pip install keras-self-attention

The trailing dl tag in squared brackets when installing sktime means you want to include the optional deep learning models available in the library.

In this recipe, we’ll use an example dataset available in sktime. We’ll load it in the next section.

How to do it…

As the name implies, the sktime library follows a design pattern similar to scikit-learn. So, our approach to building a deep learning model using sktime will be similar to the workflow...

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