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July 13th, 2020
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DELTA LAB has a user-driven, evergrowing, knowledge center for Smart Automation. It's user-driven because you can help prioritize content by leaving comments on placeholders that interest you. It's evergrowing not only because new content is consistently published, but also because it is continuously updated. In this post we go through how it works, what it will provide you, and how you can make the most out of it.
Machine Learning (ML), as any other software implementation, must be tested to ensure it behaves as expected. Even more so in the case of ML, since it produces dynamic outputs based on changing inputs which often had not been seen before by the system, it is important for ML tests to look out for model drift by performing distribution tests, for example. In this post we go through various practical techniques that should be used to test production ML systems and things to look out for.