Welcome to sktime#
A unified framework for machine learning with time series.
sktime provides an easy-to-use, flexible and modular open-source framework for a wide range of time series machine learning tasks. It offers scikit-learn compatible interfaces and model composition tools, with the goal to make the ecosystem more usable and interoperable as a whole. We build and sustain an open, diverse and self-governing community, welcoming new contributors from academia and industry through instructive documentation, mentoring and workshops.
unified API for machine learning with time series, for model specification, fitting, application, and validation
tools for composite model buildin including pipelining with transformations, ensembling, tuning and reduction
interactive user experience with scikit-learn like syntax 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
Get started using
Find user documentation.
Understand sktime’s API.
Find out how you can contribute.
Information for developers.
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