Учим избавляться от рутины во внутренних процессах жизненного цикла моделей и повышать эффективность своей работы.

AutoML in practice

Изучаются алгоритмы обучения с подкреплением, использующие нейронные сети.

Deep Reinforcement Learning (autumn 2024)

Курс про линейные модели и ансамбли из деревьев решений

Классические модели ML (autumn 2024)

Natural Language Processing (NLP) is a domain of research whose objective is to analyze and understand human languages and develop technologies to enable human machine interactions with natural languages. NLP is an interdisciplinary field involving linguistics, computer sciences and artificial intelligence. The goal of this course is to provide students with comprehensive knowledge of NLP. Students will be equiped with the principles and theories of NLP, as well as various NLP technologies, including rule-based, statistical and neural network ones. After this course, students will be able to conduct NLP research and develop state-of-the-art NLP systems.

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AutoML in practice

Deep Reinforcement Learning (autumn 2024)

Классические модели ML (autumn 2024)

Natural Language Processing course (stream 7, autumn 2024)