Introduction to Machine Learning with Time Series at PyData Festival Amsterdam 2020
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This tutorial was written for sktime version 0.4.2
.
For more up-to-date notebooks visit sktime's online documentation <https://www.sktime.org/en/latest/how_to_get_started.html>
__.
This is the repository for the "Introduction to Machine Learning with Time Series" code breakfast at PyData Festival Amsterdam 2020.
You can watch the video here: https://www.youtube.com/watch?v=Wf2naBHRo8Q
You'll learn about:
sktime <https://github.com/alan-turing-institute/sktime>
_ and scikit-learn <https://scikit-learn.org/stable/>
_),We assume familiarity with the standard tabular machine learning setting
covered by scikit-learn <https://scikit-learn.org/stable/>
_, but no prior
experience of working with time series.
You can either
pip install sktime <https://alan-turing-institute.github.io/sktime/installation.html>
_ and clone <https://help.github.com/en/github/creating-cloning-and-archiving-repositories/cloning-a-repository>
_ this repository to run the notebooks locally. This requires a working Python installation (e.g. Anaconda distribution <https://docs.anaconda.com/anaconda/install/>
) with Jupyter notebooks <https://jupyter.org/install>
.We are actively looking for contributors! Any contributions are welcome, not
just code! Please chat to us <https://gitter.im/sktime/community>
_ or raise an issue <https://github.com/alan-turing-institute/sktime/issues/new/choose>
_ if you're interested.