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> plain vanilla logistic regression

Eh? It's not as easy as it sounds. Search for "mlelr" for a rather detailed illustration of how to code LR in C with only standard libraries. Now that was some fun to put together!

But that does mean that you have pretty good C programming skills! I think your comment reinforces my claim about pairing MOOC-depth ML with other skills.

(Edit: I'm not saying MOOC-depth derisively. Serious learners and autodidacts can go pretty deep with just MOOCs for guidance. I just mean prima facie, based on content of some of the lighter and more popular MOOCs like Andrew Ng's. Abu-Mostafa's on EdX is meatier.)

I definitely agree: the overuse of techniques like logistic regression in introductory courses without sufficient mathematical background and context can lead to a "plug and chug" culture where the technique is applied without proper understanding of its assumptions and limitations.

Anyone can be quickly taught how to run a logistic regression by calling one line of code from a high level library. But I'd argue it takes years of study to really know what you're doing.

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