Seventh Machine Learning in High Energy Physics Summer School 2021

Session

Seminar

Not scheduled

Zoom

Presentation materials

learning-to-pivot.pdf

8. Course technicalities, working environment

24. Deep learning III

Mr Alexander Panin (Yandex School of Data Analysis (RU))

25. Deep learning IV

Mr Alexander Panin (Yandex School of Data Analysis (RU))

27. Deep neural networks

Alexander Panin (Yandex School of Data Analysis (RU))

16. Ensemble algorithms, dimensionality reduction

Random forest, gradient boosting, PCA

21. Feature engineering and selection

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

Flatness boosting and reweighting

17. Hyperparameters search

12. Model evaluation

Overfitting, Cross-validation

9. Python for data analysis; Probability density estimation

numpy, root_numpy, pandas, matplotlib

35. Seminar 6. Image recognition using convolutional neural networks.

32. Seminar. Computing gradient by hand. Keras.

Alexey Artemov (Yandex)

46. Seminar. Generative Adversarial Networks.

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

53. Seminar. Graph Models (MPNN).

Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))

13. Seminar. Image recognition using convolutional neural networks.

Alexey Artemov (Yandex)

41. Seminar. NN interpretation. Tips & tweaks.

Dr Alexey Artemov (Skoltech, HSE)

37. Seminar. Tensorflow, Variational Autoencoder.

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

20. Shallow neural networks

Alexander Panin (Yandex School of Data Analysis (RU))

29. Track 1 Seminar. Introduction into Decision Trees. Python ML stack recap (numpy, scikit-learn, pandas).

Maxim Borisyak (Yandex School of Data Analysis (RU))