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AA 19/20 Lecture 10
AA 19/20 Lecture 13
AA 19/20 Lecture 9
AA 19/20 Lecture 7
AA 19/20 Lecture 8
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AA 19/20 Lecture 10

AA 19/20 Lecture 10

SVM: soft margins, kernel trick, overfitting and regularization. Assignment 1.

AA 19/20 Lecture 13

AA 19/20 Lecture 13

Empirical Risk Minimization. Decision theory. Probably Approximately Correct Learning. VC dimension and shattering.

AA 19/20 Lecture 9

AA 19/20 Lecture 9

Maximum Margin Classifiers. Support vector machines for linear classification.

AA 19/20 Lecture 7

AA 19/20 Lecture 7

Generative models: naive bayes, bayes. Comparing classifiers.

AA 19/20 Lecture 8

AA 19/20 Lecture 8

Read more details and related context about AA 19/20 Lecture 8.