While Model Trains

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

"Just get some labelled data"

Neal Lathia

"This is just a small ode to the folks who spend countless hours on the toil that is 'just' getting some labelled data."

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A smooth approach to putting machine learning into production

Max Halford

"In online machine learning, the idea is that your model is only allowed to learn from one example at a time. This is contrast to batch learning where all the available data is processed at once."

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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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