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How to Trust Your Deep Learning Code


Speaker:: Tilman Krokotsch

Track: PyData: Deep Learning Errors in Deep Learning are hard to catch as training often fails silently s. Unit testing can catch those errors early and lets you make changes to your code base with confidence. Learn about the unique challenges of testing Deep Learning systems and how to trust your code again with hands-on examples explained on a realistic Deep Learning repository.

Recorded at the PyConDE & PyData Berlin 2022 conference, April 11-13 2022. More details at the conference page: Twitter: Twitter:


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