While Model Trains

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

One year as a Data Scientist at Stack Overflow

David Robinson

A story about the first year of working at Stack Overflow after transitioning from academia.

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Useful Python decorators for Data Scientists

Marton Trencseni

Six decorators that are useful for data scientists working with notebooks.

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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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