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be5b33kui
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2019/05/20 12:33 hoffmmat
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2019/05/20 12:33 hoffmmat
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courses:be5b33kui:lectures:start [2019/05/20 12:33]
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courses:be5b33kui:lectures:start [2019/05/20 12:33]
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| 06.05.2019 | 12 | Bayesian classification and decisions. {{ :courses:be5b33kui:lectures:10_bayes_withnotes.pdf |}} |
| 06.05.2019 | 12 | Bayesian classification and decisions. {{ :courses:be5b33kui:lectures:10_bayes_withnotes.pdf |}} |
| 13.05.2019 | 13 | Bayesian classification, ROC characteristics, k-nn and relationship to Bayesian classifier. {{ :courses:be5b33kui:lectures:11_recog_a_withnotes.pdf |}} {{ :courses:be5b33kui:lectures:11_recog_b_withnotes.pdf |}} |
| 13.05.2019 | 13 | Bayesian classification, ROC characteristics, k-nn and relationship to Bayesian classifier. {{ :courses:be5b33kui:lectures:11_recog_a_withnotes.pdf |}} {{ :courses:be5b33kui:lectures:11_recog_b_withnotes.pdf |}} |
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| 20.05.2019 | 14 | Classification in feature space. Discriminant functions. Linear separability. Nearest neighbor classification. Perceptron algorithm. {{ :courses:be5b33kui:lectures:11_recog_b_withnotes.pdf |}}. Maximum likelihood estimation - very brief intro (15 min.), not for exam.
{{ :courses:be5b33kui:lectures:12_mle_withnotes.pdf |}}
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| 20.05.2019 | 14 | Classification in feature space. Discriminant functions. Linear separability. Nearest neighbor classification. Perceptron algorithm. {{ :courses:be5b33kui:lectures:11_recog_b_withnotes.pdf |}}. Maximum likelihood estimation - very brief intro (15 min.), not for exam. |
courses/be5b33kui/lectures/start.txt
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