"The difficulty is that machine learning is a fundamentally hard debugging problem. Debugging for machine learning happens in two cases: 1) your algorithm doesn't work or 2) your algorithm doesn't work well enough."
Read it!Prediction intervals are commonly used for linear models but are often underused for random forests. Leveraging the fact that a random forest can provide a conditional distribution instead of just the conditional mean makes prediction intervals relatively straightforward to use in this context.
Read it!"Even though I’m one of the beneficiary of this AI craze, I can’t help but thinking this will burst. I don’t know how and when, but I have this belief that the system is currently being rigged in favor of people whose resumes dotted with fancy keywords like mine, and a rigged system can’t be sustainable."
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