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Kevin Lemagnen: Maintainable code in data science | PyData London 2019 Video

Github Exercises and Slides - https://github.com/klemag/pydataLDN_2019-maintainable-code-for-data-science

Notebooks are great, they allow to explore your data and prototype models quickly. But they make it hard to follow good software practices. In this tutorial, we will go through a case study.We will see how to refactor our code as a testable and maintainable Python package with entry-points to tune, train and test our model so it can easily be integrated to a CI/CD flow.

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Users can upload, view, rate, share, and comment on videos, with content spanning video clips, music videos, live streams, and more.

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