A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python

A unified framework for machine learning with time series

A multiverse of Prophet models for timeseries

Base classes for creating scikit-learn-like parametric objects, and tools for working with them.

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A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.

Time series anomaly detection, time series classification & dynamic time warping, performed on a dataset of Canadian weather measurements.

🧱 Wrappers for 3rd party models to be used with fold (https://github.com/dream-faster/fold)

forecasting library, extend sktime

The second attempt at tne multinomial series. Not for commercial use.

An easy and effective application to get insights and predict the future.