modality:time-series
Time Series
Time Series in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
Forecasting & temporal ML
Forecast contracts and naive models
A forecast begins with two clocks—when you know and when you predict—and a baseline that respects both.
Forecasting & temporal MLTrend, seasonality, and known-future signals
A temporal feature is valid only if its value could be reconstructed exactly at the forecast origin.
Forecasting & temporal MLBacktesting without time travel
A faithful backtest is a replay of past information states, not merely a sorted split.
Forecasting & temporal MLStatistical and ML forecasters
Choose a forecaster and a multi-step strategy together; the estimator alone does not define the forecast.
Forecasting & temporal MLIntervals, drift, and forecast operations
Forecast reliability is the joint discipline of calibrated ranges, drift evidence, and a usable fallback.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.