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- November 2025
- ISBN 9781633435896
- 256 pages
- printed in black & white
print book available Nov 25, 2025
ePub + liveBook available Nov 25, 2025
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Look inside
Make accurate time series predictions with powerful pretrained foundation models!
You don’t need to spend weeks—or even months—coding and training your own models for time series forecasting. Time Series Forecasting Using Foundation Models shows you how to make accurate predictions using flexible pretrained models.
In Time Series Forecasting Using Foundation Models you will discover:
Time Series Forecasting Using Foundation Models teaches you how to do efficient forecasting using powerful time series models that have already been pretrained on billions of data points. You’ll appreciate the hands-on examples that show you what you can accomplish with these amazing models. Along the way, you’ll learn how time series foundation models work, how to fine-tune them, and how to use them with your own data.
You don’t need to spend weeks—or even months—coding and training your own models for time series forecasting. Time Series Forecasting Using Foundation Models shows you how to make accurate predictions using flexible pretrained models.
In Time Series Forecasting Using Foundation Models you will discover:
- The inner workings of large time models
- Zero-shot forecasting on custom datasets
- Fine-tuning foundation forecasting models
- Evaluating large time models
Time Series Forecasting Using Foundation Models teaches you how to do efficient forecasting using powerful time series models that have already been pretrained on billions of data points. You’ll appreciate the hands-on examples that show you what you can accomplish with these amazing models. Along the way, you’ll learn how time series foundation models work, how to fine-tune them, and how to use them with your own data.
about the technology
Time-series forecasting is the art of analyzing historical, time-stamped data to predict future outcomes. Foundational time series models like TimeGPT and Chronos, pre-trained on billions of data points, can now effectively augment or replace painstakingly-built custom time-series models.about the book
Time Series Forecasting Using Foundation Models explores the architecture of large time models and shows you how to use them to generate fast, accurate predictions. You’ll learn to fine-tune time models on your own data, execute zero-shot probabilistic forecasting, point forecasting, and more. You’ll even find out how to reprogram an LLM into a time series forecaster—all following examples that will run on an ordinary laptop.what's inside
- How large time models work
- Zero-shot forecasting on custom datasets
- Fine-tuning and evaluating foundation models
about the reader
For data scientists and machine learning engineers familiar with the basics of time series forecasting theory. Examples in Python.about the author
Marco Peixeiro builds cutting-edge open-source forecasting Python libraries at Nixtla. He is the author of Time Series Forecasting in Python.eBook
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Clear and hands-on, featuring both theory and easy-to-follow examples.
Bridges the gap between classical forecasting methods and the new developments in the foundational models. A fantastic resource.
A foundational guide to forecasting’s next chapter.
An immensely practical introduction to forecasting using foundation models.
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