AI for Time Series Forecasting

AI for time-series forecasting combines classical statistical models with sequence models to predict future values and quantify uncertainty. Practical approaches include ARIMA baselines, RNN/Transformer architectures, walk-forward validation, and probabilistic losses (quantile, CRPS) for uncertainty-aware forecasts.