Introduction to Machine Learning and Data Mining
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Версия от 10:25, 22 февраля 2019; Machine (обсуждение | вклад)
Lecturers: Dmitry Ignatov
TAs: Ivan Zaputliaev (Module 3 and 4), Alexander Korabelnikov (Module 4).
Lecture on 23.01.2019
Intro slides.
Practice: demonstration with Orange.
Lecture on 06.02.2019
Slides: Introduction to classification techniques (1-rule, kNN, Naive Bayes, Logistic Regression).
Practice: demonstration with Orange and scikit-learn.
Lecture on 22.02.2019
Practice with scikit-learn (kNN, Naive Bayes, Logistic Regression, basic quality metrics, cross-validation, error plots)
Slides: Decision trees. Entropy and information gain. ID3 algorithm. Gini impurity. Tree pruning.