This repository was created for DL seminars taught at HSE for first-year undergraduates in the Data Science program. The seminars is an addition to the lecture course by Sergey Nikolenko: https://logic.pdmi.ras.ru/~sergey/teaching/mlspsu2022.html
The seminars contain material on topics:
- Introduction to numpy,
- Visualization libraries,
- Introduction to Pandas,
- Itroduction to the classification problem,
- Decision trees, KNN models,
- Linear models, regularization,
- Learning metrics,
- Bagging,
- Feature importance,
- PCA, K-means,
- as well as a discussion of ordinary problems from interviews and their solution.
Used links for seminars:
- YDSA ML Handbook : https://academy.yandex.ru/handbook/ml
- New articles, SoTA code : https://arxiv.org/ , https://www.researchgate.net/ , https://paperswithcode.com/sota
- Interview resources : https://github.com/cdeweyx/DS-Career-Resources/blob/master/Interview-Resources.md
The continuation of the course will be Deep Learning in the 3rd, 4th modules of the first-year DS program.