Forecasting Methods & Evaluation Library

A practical catalog of forecasting algorithms, error metrics, backtesting patterns, and model-selection guidance to move forecasts from experiments into repeatable operations.


Guide

Selecting Forecasting Algorithms: Practical, Operational Guide

Practical guidance to choose forecasting approaches based on data size, seasonality, horizon, and explainability needs. Includes a decision logic map, data preparation tips, when to prefer probabilistic forecasts, worked examples, common pitfalls, and an operational evaluation checklist.

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