For those who prefer to have a proper date column.

Various exponential smoothing models implemented in pandas

Uses DeepNPTS to generate predictions

Uses LightGBM to generate predictions

Uses AutoETS to generate predictions

This notebook demonstrates univariate time series modeling using the fable package in R. It includes data preparation, exploratory analysis, and the development of multiple forecasting models (sNaive, ARIMA, ETS, Mean, and Drift) with parallel processing, followed by forecast accuracy evaluation.

Learn about a new algorithm on the scene and get a good score along the way!

This notebook describes how ETS/iETS from the smooth package in R can be used to produce forecasts. The score is 0.613417419243

Use Polars expressions with statsforecast to generate predictions