Time Series Forecasting Using Foundation Models

Author:   Marco Peixeiro
Publisher:   Manning Publications
ISBN:  

9781633435896


Pages:   256
Publication Date:   25 December 2025
Format:   Hardback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Time Series Forecasting Using Foundation Models


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Full Product Details

Author:   Marco Peixeiro
Publisher:   Manning Publications
Imprint:   Manning Publications
Dimensions:   Width: 18.80cm , Height: 1.40cm , Length: 23.60cm
Weight:   0.450kg
ISBN:  

9781633435896


ISBN 10:   163343589
Pages:   256
Publication Date:   25 December 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

PART 1: THE RISE OF FOUNDATION MACHINE LEARNING MODELS  1 UNDERSTANDING FOUNDATION MODELS  2 BUILDING A FOUNDATION MODEL  PART 2: FOUNDATION MODELS DEVELOPED FOR FORECASTING  3 FORECASTING WITH TIMEGPT  4 ZERO-SHOT PROBABILISTIC FORECASTING WITH LAG-LLAMA  5 LEARNING THE LANGUAGE OF TIME WITH CHRONOS  6 MOIRAI: A UNIVERSAL FORECASTING TRANSFORMER  7 DETERMINISTIC FORECASTING WITH TIMESFM  PART 3: LEVERAGE LLMS FOR TIME SERIES FORECASTING  8 FORECASTING AS A LANGUAGE TASK  9 REPROGRAM AN LLM FOR FORECASTING  PART 4: CAPSTONE PROJECT  10 CAPSTONE PROJECT: FORECASTING DAILY VISITS TO A BLOG

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Author Information

Marco Peixeiro is a renowned data-science educator known for demystifying complex forecasting techniques. With years developing open-source libraries at Nixtla, Marco brings clarity, practicality, and enthusiasm to every page. He distills cutting-edge research into step-by-step guidance that helps readers deliver accurate forecasts quickly.

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