Information Theory, Pattern Recognition, and Neural Networks
Jakob Foerster
Why watch
David MacKay's Cambridge lectures, the companion to his free textbook.
This is a full series. The player starts at the first episode; use its playlist menu, or open it on YouTube, to pick an episode.
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32:203Blue1BrownReinventing Entropy | Compression is Intelligence Part 1
Derives entropy from scratch, framed around prediction and compression.
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33:513Blue1BrownBut what is cross-entropy? | Compression is Intelligence Part 2
The loss every language model minimizes, and its link to compression.
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5:13Adian LiusieIntuitively Understanding the KL Divergence
A five-minute intuition for KL as the gap between cross-entropy and entropy.
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30:383Blue1BrownSolving Wordle using information theory
Entropy as expected information gain, applied to a game.
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