Slides & Code

This tutorial will make use of the aeon toolkit for its code examples. aeon is an open source, scikit-learn compatible framework for time series machine learning. We aim to implement the latest advances in the fields of time series machine learning, and most of the algorithms shown here will be available through aeon.

The code examples will be provided in Jupyter notebooks, which will be available for each topic. All the notebooks and slides are available on this GitHub repository. A slide and notebook file is available for each tutorial section, split up into 8 parts.

Links to individual slides and notebooks are provided on the schedule page, as well as links to the Google Colab versions of the notebooks. We also provide the links below:

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