Machine Learning at MIPT
Basic (first semester) and advanced (second semester) tracks, Spring 2021
This course aims to introduce students to modern state of Machine Learning andArtificial Intelligence. It is designed to take one year (two terms at MIPT) -approximately 2 * 15 lectures and seminars.
All learning materials are available here, full list of topics considered in thecourse are listed in program_*.pdf files.
Organizational information about current launches available atml-mipt.github.io
Repository structure
- on
masterbranch previous term materials are stored to give a quick andcomprehensive overview - on
*_basicand*_advancedbranches materials for current launches arebeing published - tags (e.g.
2021_spring) contain previous launches materials for convenience
Video lectures
All lecture materials are currently in Russian language
| Track | Launch | Lectures | Practice | Language |
|---|---|---|---|---|
| basic | Spring 2020 | youtube | youtube | ru |
| advanced | Fall 2020 | youtube | youtube | ru |
| basic | Spring 2019 | youtube | - | ru |
| advanced | Fall 2019 | youtube | youtube | ru |
Prerequisites
We are expecting our students to have a basic knowlege of:
- calculus, especially matrix calculus, differentiation
- linear algebra
- probability theory and statistics
- programming, especially on Python
Although if you don't have any of this, you could substitude it with yourdiligence because the course provides additional materials to study requirementsyourself.
Materials for self-study
A lot of great materials are available online. Seeextra materials file for the whole list.Also lectures andseminars contains references to more detailed materials on topics.
Lectures conspects are available for both basicand advanced. Especially useful for fast andfurious exam passing. (Previous version of informal basic conspect isavailable)
Docker image
Using docker for tasks evaluation is a good idea, prebuilt image is undercunstruction.
