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Jul 13, 2023 at 6:04 comment added J-J-J In addition, it might be worth asking your question on hsm.stackexchange.com , though I'm not familiar with this other website. Anyway, there may be historical/sociological causes to some statistical concepts not being taught in ML textbooks. While ML and statistics practitionners & researchers may have an essential insight into this, a social scientist could investigate it more systematically.
Jul 8, 2023 at 6:47 comment added J-J-J You might find this other question and its answer interesting, relative to why oversampling/weighting as in survey design is not used in machine learning: stats.stackexchange.com/questions/611423/…
Jul 8, 2023 at 2:02 history edited User1865345 CC BY-SA 4.0
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Jul 8, 2023 at 1:24 comment added user225256 This question does not require or develop statistical expertise in the way that I would expect for a good question on this site. But I asked ChatGPT: “What are some common concepts in statistics that are not used much in machine learning?” Since I got a reasonable answer, I recommend that as a way to start. Have you asked there or somewhere similar, and if so what did you think of the response?
Jul 8, 2023 at 1:10 comment added Dave I am curious to see responses but also fear that this is too opinion-based to be a good fit for Cross Validated. After all, there is far from a consensus about where machine learning ends and statistics begins. People also have very different approaches to learning machine learning, and it would not be so unusual for someone to jump straight into Keras without learning OLS linear regression, yet plenty of machine learning practitioners know OLS just fine.
Jul 8, 2023 at 0:49 history asked Curaçao Hajek CC BY-SA 4.0