A unified framework for machine learning with time series.
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- unified API for ML/AI with time series, for model building, fitting, application, and validation
- support for a variety of learning tasks including
forecasting <forecasting_ref>,time series classification <classification_ref>,regression <regression_ref>,clustering <clustering_ref>. - composite model building, including pipelines with transformations, ensembles, tuning, reduction
- interactive user experience with scikit-learn like interface conventions
- In-memory computation of a single machine, no distributed computing
- Medium-sized data in pandas and NumPy based containers
- Modular, principled and object-oriented API
- Using interactive Python interpreter, no command-line interface or graphical user interface
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