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I'm no data scientist but many statistical methods rely on prior knowledge and even computed inputs.

Two examples I can think of are doing linear regression on the square of your input. For deep learning, people have improved visual representation by taking samples of the colors at various frequencies. [1]

[1]: https://arxiv.org/pdf/2003.08934.pdf



Yeah, that's a better way of saying what I meant by managing the data. Mentally projecting data through, massaging said data, and building reproducible pipelines rather than manually tweaking the learned weights after the fact.




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