aeon is a Python library for time series machine learning (TSML) that provides a unified interface for various tasks including forecasting, classification, clustering, and regression. It follows the scikit-learn API to facilitate integration with existing tools and supports a wide range of time series algorithms, including efficient implementations of the latest research. The library is designed to be modular, with algorithms grouped by learning tasks, and uses object-oriented design to align with the scikit-learn estimator interface. It also includes a variety of utilities, transformations, and distance measures tailored for time series data. aeon integrates optional dependencies to provide access to additional packages such as statsmodels, tensorflow, and tsfresh, enabling the creation of wrappers for algorithms and frameworks for estimators like deep learners. The library supports Python versions 3.8 and above and is available under the 3-Clause BSD license. It includes modules for forecasting, classification, clustering, regression, and experimental tasks such as segmentation, anomaly detection, and similarity search. aeon aims to provide a comprehensive toolkit for time series machine learning, facilitating reproducible research and supporting a wide range of tasks in the field.aeon is a Python library for time series machine learning (TSML) that provides a unified interface for various tasks including forecasting, classification, clustering, and regression. It follows the scikit-learn API to facilitate integration with existing tools and supports a wide range of time series algorithms, including efficient implementations of the latest research. The library is designed to be modular, with algorithms grouped by learning tasks, and uses object-oriented design to align with the scikit-learn estimator interface. It also includes a variety of utilities, transformations, and distance measures tailored for time series data. aeon integrates optional dependencies to provide access to additional packages such as statsmodels, tensorflow, and tsfresh, enabling the creation of wrappers for algorithms and frameworks for estimators like deep learners. The library supports Python versions 3.8 and above and is available under the 3-Clause BSD license. It includes modules for forecasting, classification, clustering, regression, and experimental tasks such as segmentation, anomaly detection, and similarity search. aeon aims to provide a comprehensive toolkit for time series machine learning, facilitating reproducible research and supporting a wide range of tasks in the field.