[abhgh]

Highly recommend his blog [1] - where he often writes bite-sized math-y articles. I have personally benefited from it; I was looking for ways to sample quickly from a mixture of Beta distributions when I stumbled upon his post on the Kumaraswamy distribution [2], which takes on Beta-like shapes but has a closed form expression for the cumulative distribution function (CDF). The latter property makes generating samples from it convenient and fast.

[1] https://www.johndcook.com/blog/

[2] https://www.johndcook.com/blog/2009/11/24/kumaraswamy-distri...

[pixelpoet]

+1, learnt soooo much from it. I have this mentally categorised next to Paul Bourke's website, which was one of the best sources of information in 90s internet: http://paulbourke.net/

[oarabbus_]

I can't count how many times I'd be looking up a statistical or applied mathematical concept and came across an article he'd written on it. Great resource.

[jofer]

In addition to being a great resource on mathematics and scientific computing in general, if you're working in the scientific python ecosystem, his blog (and assorted similar content on twitter/etc) is a must-read. There's often a lot of great scientific python content there too.

[malshe]

I love his blog. It has wealth of information.