You're reading from Modern Time Series Forecasting with Python Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas

Product type Paperback

Published in Oct 2024

Publisher Packt

ISBN-13 9781835883181

Length 658 pages

Edition 2nd Edition

Languages

Python

Tools

PyTorch

Concepts

Data Science

Authors (2):

Jeffrey Tackes

Manu Joseph

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Table of Contents (26) Chapters

Preface

1. Part-1: Getting Familiar with Time Series FREE CHAPTER

2. Introducing Time Series

3. Acquiring and Processing Time Series Data

4. Analyzing and Visualizing Time Series Data

5. Setting a Strong Baseline Forecast

6. Part-2: Machine Learning for Time Series

7. Time Series Forecasting as Regression

8. Feature Engineering for Time Series Forecasting

9. Target Transformations for Time Series Forecasting

10. Forecasting Time Series with Machine Learning Models

11. Ensembling and Stacking

12. Global Forecasting Models

13. Part-3: Deep Learning for Time Series

14. Introduction to Deep Learning

15. Building Blocks of Deep Learning for Time Series

16. Common Modeling Patterns for Time Series

17. Attention and Transformers for Time Series

18. Strategies for Global Deep Learning Forecasting Models

19. Specialized Deep Learning Architectures for Forecasting

20. Probabilistic Forecasting and More

21. Part-4: Mechanics of Forecasting

22. Multi-Step Forecasting

23. Evaluating Forecast Errors—A Survey of Forecast Metrics

24. Evaluating Forecasts—Validation Strategies

25. Index

What is attention?

The idea of attention was inspired by human cognitive function. At any moment, the optic nerves in our eyes, the olfactory nerves in our noses, and the auditory nerves in our ears send a massive amount of sensory input to the brain. This is way too much information, definitely more than the brain can handle. But our brains have developed a mechanism that helps us to pay attention to only the stimuli that matter—such as a sound or a smell that doesn’t belong. Years of evolution have trained our brains to pick out anomalous sounds or smells because that was key for us surviving in the wild, where predators roamed free. In cognitive science, attention is defined as the cognitive process that allows an individual to selectively focus on specific information while ignoring other irrelevant stimuli.

Apart from this kind of instinctive attention, we are also able to control our attention by what we call focusing on something. You are doing it right now...

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You're reading from Modern Time Series Forecasting with Python Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas

Table of Contents (26) Chapters

What is attention?

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Authors (2)

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