What’s different about time series forecasting compared to standard ML?

Time series has temporal dependency. Differences: - Use time-based splits - Handle seasonality and trends - Create lag/rolling features - Evaluate with horizon-aware metrics Forecasting failures often come from leakage and ignoring non-stationarity. Always baseline with naive forecasts.