Time Series Forecasting Using Foundation Models

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Time Series Forecasting Using Foundation Models

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Author : Marco Peixeiro
language : en
Publisher: Simon and Schuster
Release Date : 2025-12-16

Time Series Forecasting Using Foundation Models written by Marco Peixeiro and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-16 with Computers categories.

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: • 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. Table of Contents Part 1 1 Understanding foundation models 2 Building a foundation model Part 2 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 8 Forecasting as a language task 9 Reprogramming an LLM for forecasting Part 4 10 Capstone project: Forecasting daily visits to a blog Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.

Time Series Forecasting Using Generative Ai

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Author : Banglore Vijay Kumar Vishwas
language : en
Publisher: Springer Nature
Release Date : 2025-03-24

Time Series Forecasting Using Generative Ai written by Banglore Vijay Kumar Vishwas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-24 with Mathematics categories.

"Time Series Forecasting Using Generative AI introduces readers to Generative Artificial Intelligence (Gen AI) in time series analysis, offering an essential exploration of cutting-edge forecasting methodologies." The book covers a wide range of topics, starting with an overview of Generative AI, where readers gain insights into the history and fundamentals of Gen AI with a brief introduction to large language models. The subsequent chapter explains practical applications, guiding readers through the implementation of diverse neural network architectures for time series analysis such as Multi-Layer Perceptrons (MLP), WaveNet, Temporal Convolutional Network (TCN), Bidirectional Temporal Convolutional Network (BiTCN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Deep AutoRegressive(DeepAR), and Neural Basis Expansion Analysis(NBEATS) using modern tools. Building on this foundation, the book introduces the power of Transformer architecture, exploring its variants such as Vanilla Transformers, Inverted Transformer (iTransformer), DLinear, NLinear, and Patch Time Series Transformer (PatchTST). Finally, The book delves into foundation models such as Time-LLM, Chronos, TimeGPT, Moirai, and TimesFM enabling readers to implement sophisticated forecasting models tailored to their specific needs. This book empowers readers with the knowledge and skills needed to leverage Gen AI for accurate and efficient time series forecasting. By providing a detailed exploration of advanced forecasting models and methodologies, this book enables practitioners to make informed decisions and drive business growth through data-driven insights. !-- [if !supportLists]--● !--[endif]--Understand the core history and applications of Gen AI and its potential to revolutionize time series forecasting. !-- [if !supportLists]--● !--[endif]--Learn to implement different neural network architectures such as MLP, WaveNet, TCN, BiTCN, RNN, LSTM, DeepAR, and NBEATS for time series forecasting. !-- [if !supportLists]--● !--[endif]--Discover the potential of Transformer architecture and its variants, such as Vanilla Transformers, iTransformer, DLinear, NLinear, and PatchTST, for time series forecasting. !-- [if !supportLists]--● !--[endif]--Explore complex foundation models like Time-LLM, Chronos, TimeGPT, Moirai, and TimesFM. !-- [if !supportLists]--● !--[endif]--Gain practical knowledge on how to apply Gen AI techniques to real-world time series forecasting challenges and make data-driven decisions. Who this book is for: Data Scientists, Machine learning engineers, Business Aanalysts, Statisticians, Economists, Financial Analysts, Operations Research Analysts, Data Analysts, Students.

Advances In Mechatronics And Control Engineering Iii

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Author : Prasad Yarlagadda
language : en
Publisher: Trans Tech Publications Ltd
Release Date : 2014-10-08

Advances In Mechatronics And Control Engineering Iii written by Prasad Yarlagadda and has been published by Trans Tech Publications Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-08 with Technology & Engineering categories.

Selected, peer reviewed papers from the 2014 3rd International Conference on Mechatronics and Control Engineering (ICMCE 2014), August 27-28, 2014, Zhuhai, China

Nag Foundation Toolbox For Use With Matlab

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Author : MathWorks, Inc
language : en
Publisher:
Release Date : 1995

Nag Foundation Toolbox For Use With Matlab written by MathWorks, Inc and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with MATLAB categories.

A Practical Guide To Box Jenkins Forecasting

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Author : John C. Hoff
language : en
Publisher:
Release Date : 1983

A Practical Guide To Box Jenkins Forecasting written by John C. Hoff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Business & Economics categories.

Giannini Foundation Monograph

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Author : Giannini Foundation of Agricultural Economics
language : en
Publisher:
Release Date : 1972

Giannini Foundation Monograph written by Giannini Foundation of Agricultural Economics and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972 with Agriculture categories.

Transactions Of The American Society Of Civil Engineers

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Author : American Society of Civil Engineers
language : en
Publisher:
Release Date : 1986

Transactions Of The American Society Of Civil Engineers written by American Society of Civil Engineers and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Technology & Engineering categories.

Giannini Foundation Research Report

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Author : Giannini Foundation of Agricultural Economics
language : en
Publisher:
Release Date : 1986

Giannini Foundation Research Report written by Giannini Foundation of Agricultural Economics and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Agriculture categories.

Foundation Engineering

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Author : National Research Council (U.S.). Transportation Research Board
language : en
Publisher: Transportation Research Board National Research
Release Date : 1992

Foundation Engineering written by National Research Council (U.S.). Transportation Research Board and has been published by Transportation Research Board National Research this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Technology & Engineering categories.

Techniques Of Forecasting Using Vector Autoregressions

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Author : Robert B. Litterman
language : en
Publisher:
Release Date : 1979

Techniques Of Forecasting Using Vector Autoregressions written by Robert B. Litterman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Autoregression (Statistics) categories.