Entropy can be used to understand systems

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3 pointsacgan2 comments

Maximum entropy: https://en.wikipedia.org/wiki/Maximum_entropy

Here's a quote of a tweet about a (my own): comment on a schema:BlogPost: https://twitter.com/westurner/status/1048125281146421249:

> “When Bayes, Ockham, and Shannon come together to define machine learning” https://towardsdatascience.com/when-bayes-ockham-and-shannon...

> Comment: "How does this relate to the Principle of Maximum Entropy? How does Minimum Description Length relate to Kolmogorov Complexity?"

Thanks for sharing! Despite the fact that Shannon's "A Mathematical Theory of Communication" is so accessible, I find that most in our field (stats/ML) don't often think through information-theoretic tools in a "first principles way."

Yes, KL divergences show up everywhere, but they are not derived from scratch often enough. Maybe I'm stifled by my campus bubble though :)

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