Дизайн систем машинного обучения. Введение для начинающих.

ML System Design. Autumn 23/24

ML System Design. Autumn 22/23

Graph Machine Learning is the science between graph theory and machine learning. It is now a very active area of research, with hundreds of publications each month, impactful applications in the industry, and new insights about our world. Intersection of graph theory and machine learning. Overview, SOTA, applications.

Graph ML

Интерпретация моделей машинного обучения: как объяснить результаты статистических моделей заказчику.

Interpretable ML

Трек посвящен методам управления Data Science проектами.

Lean Data Science

A tutorial on uncertainty estimation in ML for a non-research practitioners of machine learning. Will cover basics of uncertainty estimation via ensemble methods, ensemble-emulation methods and generative methods. We will also provide a detailed case-study of an example usage of uncertainty estimation.

Uncertainty Estimation in ML

Welcome to the Machine Learning REPA: Reproducibility, Experiments and Pipelines Automation!

ML REPA

Reinforcement Learning in a Nutshell. Games, articles, production - choose wisely.

Reinforcement Learning

Машинное обучение в реальных секторах экономики - от добычи нефти до генерации энергии и производства стали.

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