While Model Trains

Read data blog posts.
Carefully handpicked.
Presented 3 at a time.

Confession of a so-called AI expert

Chip Huyen

"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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Variance after scaling and summing: One of the most useful facts from statistics

Chris Said

"What do R2, laboratory error analysis, ensemble learning, meta-analysis, and financial portfolio risk all have in common? The answer is that they all depend on a fundamental principle of statistics that is not as widely known as it should be. Once this principle is understood, a lot of stuff starts to make more sense."

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Nitpicking Machine Learning Technical Debt

Matthew McAteer

25 best practices to mitigate technical debt in machine learning.

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