2023/2024
Bayesian Methods for Machine Learning
Type:
Mago-Lego
Delivered by:
Big Data and Information Retrieval School
When:
1, 2 module
Online hours:
52
Open to:
students of one campus
Language:
English
ECTS credits:
6
Contact hours:
10
Course Syllabus
Abstract
Bayesian methods in machine learning are based on the so-called Bayesian approach for statistics, one of the possible ways to conduct mathematical reasoning under uncertainty. In application to ML models Bayesian methods allow to consider user preferences when building decision rules for prediction and make this efficient. In addition, solving problems of selecting models’ structure parameters (number of clusters, coefficient of regularization etc) becomes possible without full combinatorial search. This 6-week course is an introduction to Bayesian Methods. At the same time, it covers the most important topics in practice.
To complete the course, students are supposed to have skills in basic mathematical courses (calculus, linear algebra), probability theory, programming in Python and basic machine learning models.