While Model Trains

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

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."

Read it!

A Framework for Making Decisions with Data

Caitlin Hudon

A five-step method for transitioning from problem to data-backed decision making.

Read it!

Finding bad flamingo drawings with recurrent neural networks

Colin Morris

Using Sketch-RNN as a probability estimator to identify the worst sketches of flamingos in 'Quick, Draw!'.

Read it!