Machine Learning for a Model Construction

2023/2024

Academic Year

RUS

Instruction in Russian

3

ECTS credits

Delivered at:

School of Applied Mathematics

Course type:

Compulsory course

When:

1 year, 4 module

Instructor

Ratnikov, Fedor

Программа дисциплины

Аннотация

The course introduces the students to mathematical modeling using machine learning techniques, including supervised and unsupervised methods such as linear and logistic regressions, decision trees, bootstrapping, random forests, boosting, regularized methods and several topics in deep learning, such as artificial neural networks, convolutional neural networks, transformers and auto-encoders, etc. The course uses Google Colaboratory, GitHub Classroom, and DataCamp products and services and aims to raise practical skills in using machine learning methods to solve typical problems of mathematical modeling.