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Welcome to the documentation for aeon#

  • Framework for time series tasks such as forecasting and classification.

  • Extends the scikit-learn interface, allowing for ease of use for familiar users.

  • Provides a library of time series algorithms rather than a curated selection.

  • Efficient implementation of time series algorithms using numba.

  • Interfaces with other time series packages to provide a single framework for algorithm comparison.

  • Uses a system of optional dependencies to allow easy installation of basic functionality.


Get started with time series forecasting.


Get started with time series classification.


Get started with time series extrinsic regression.


Get started with time series clustering.


Get started with time series transformations.

Community Channels#


Slack: aeon slack

Twitter: twitter/aeon-toolkit

LinkedIn: linkedin/aeon-toolkit