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Shreya Shankar
sh_reya
Unit testing for ML pipelines is challenging given changing data, features, models, etc. Changing I/O make it hard to have fixed unit tests. To hackily get around this, I liberally
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practical MLE tip: if you know your distribution isn’t Gaussian, min-max normalize instead of standardizehttps://twitter.com/svpino/status/1318930792232456192 practical deep learning tip: if you have serious outliers in your dataset, you
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In good software practices, you version code. Use Git. Track changes. Code in master is ground truth.In ML, code alone isn't ground truth. I can run the same SQL query
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Here are some lowlights from my reading of TikTok security reports[1] (for the record, you can learn to avoid these in an intro security or privacy class):[1] https://penetrum.com/research The Android
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Got my invite to the @OpenAI GPT-3 API from @gdb. I actually think it deserves more hype than it’s getting, but not necessarily for the magical reasons Twitter touts. Why?
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I 100% recommend this @karpathy talk about multi-task learning at scale. @ericjang11 covers some of the main points well.But as the 1st ML engineer at a startup that sells an
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