Marco Peixeiro

Time Series Forecasting Using Foundation Models

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.

Getting Started with Time Series Forecasting in Python

Marco Peixeiro explores the random walk model, MA(q), and AR(p) models, and teaches you how to use the ACF and PACF plots for forecasting.