Math & Optimization · beginner · concept 39 of 176
Probability & Bayes' Theorem
Machine learning is applied probability: models output distributions, training maximizes likelihood, and Bayes' theorem tells you how to update belief when evidence arrives. It is also the antidote to the classic diagnostic fallacy, a positive test for a rare disease usually still means you are fine.
Key terms
Conditional probabilityPrior and posteriorLikelihoodDistributionsExpectation
Where you meet it in the real world
Spam filters, medical diagnosis, language model sampling, risk models, A/B test analysis
Videos
▶ Bayes theorem, the geometry of changing beliefs ↗
3Blue1Brown · YouTube
▶ Bayes' Theorem, Clearly Explained!!!! ↗
StatQuest with Josh Starmer · YouTube
Guides and articles
Seeing Theory ↗
Seeing Theory (Brown University)
Mathematics for Machine Learning | Companion webpage to the book “Mathematics for Machine ↗
Mathematics for Machine Learning (free book)
Courses, papers, and more
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