MLHEP 2015 summer school

27–30 Aug 2015

Academic University

Europe/Moscow timezone

Session

Introductory track

27 Aug 2015, 09:40

Academic University

Academic University

Khlopin st, 8, Saint Petersburg, Russia

Introductory track: lectures

Alexey Rogozhnikov

Introductory track: seminars

Nikita Kazeev (Yandex School of Data Analysis (RU))

Introductory track: lectures #2

Alexey Rogozhnikov

Introductory track: seminars #2

Nikita Kazeev (Yandex School of Data Analysis (RU))

Introductory track: lectures #3

Alexey Rogozhnikov

Introductory track: seminars #3

Nikita Kazeev (Yandex School of Data Analysis (RU))

Introductory track: lectures #4

Alexey Rogozhnikov

Introductory track: seminars #4

Nikita Kazeev (Yandex School of Data Analysis (RU))

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3. Intro: General pipeline, ML at a glance

27/08/2015, 09:40
4. Intro: kNN, basic overfitting, roc curve, logistic regression

27/08/2015, 11:20
7. Introduction, course technicalities

27/08/2015, 13:45
8. NumPy, Pandas, Matplotlib

27/08/2015, 15:40
11. neural networks

28/08/2015, 09:30
12. decision tree, regression tree

28/08/2015, 11:10
15. Overfitting, Cross-validation

28/08/2015, 13:45
16. Sklearn: KNN, decision tree, logistic regression

28/08/2015, 15:40
20. Ensembles

29/08/2015, 09:30
21. Gradient boosting; boosting to uniformity.

29/08/2015, 11:10
24. Ensemble algorithms: random forest, gradient boosting

29/08/2015, 13:45
25. Hyperparam Optimization

29/08/2015, 15:40
29. GBDT tuning, reweighting, testing hypotheses, gaussian processes for optimization

30/08/2015, 09:00
30. Unsupervised learning, Latent Dirichlet Allocation, PCA. Fast predictions and pruning

30/08/2015, 10:40
33. PCA, RBM and alike on MNIST

30/08/2015, 13:00
34. Clustering

30/08/2015, 14:45

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