Better machine learning by thinking like a statistician. About model interpretation, paying attention to data, and always staying critical.
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Issues | 80 | Subscribers | Read | mindfulmodeler.substack.com |
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When asked what I work on, I often have to explain what machine learning is.
Machine learning and domain expertise sometimes don’t align.
We’ve all been there: You’ve set up a machine learning pipeline with tuning, model selection, and evaluation. Tons of data splitting, maybe with cross-validation. You are done modeling and need a final model to deploy.
My approach to reading ML papers had been a constant frustration. Especially during my Ph.D., I tried different systems, but it mostly was a mix of “just remember the paper contents“, “maybe I’ll find this one relevant paper again after an ...
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The writers behind this newsletter.
Writer and machine learning expert
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