While Model Trains

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

Recommendations

Simon Hørup Eskildsen

Cool explanation of computational aspects of recommendations avoiding to "get lost in the weeds of linear algebra".

Read it!

A few reasons to be skeptical of machine learning

Julia Evans

"why, even though machine learning is really awesome and cool and you can do super powerful and interesting things with it – why you should still be skeptical"

Read it!

From both sides now: the math of linear regression

Katherine Bailey

A journey starting from the standard formulation of linear regression, moving on to the probabilistic approach, and then progressing to Bayesian linear regression.

Read it!