
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.

Forecasting
Get started with time series forecasting.

Classification
Get started with time series classification.

Regression
Get started with time series extrinsic regression.

Clustering
Get started with time series clustering.

Transformation
Get started with time series transformations.
Community Channels#
GitHub: github.com/aeon-toolkit/aeon
Slack: aeon slack
Twitter: twitter/aeon-toolkit
LinkedIn: linkedin/aeon-toolkit