Интеллектуальный анализ данных (О.Ю. Бахтеев, В.В. Стрижов)/Осень 2022
Материал из MachineLearning.
Each Saturday 13:10 at the channel m1p.org/go_zoom
Intelligent data analysis
This course delivers methods of model selection in machine learning and forecasting. The modelling data are videos, audios, encephalograms, fMRIs and another measurements in natural science. The models are linear, tensor, deep neural networks, and neural ODEs. The practical examples are brain-computer interfaces, weather forecasting and various spatial-time series forecasting. The lab works are organised as paper-with-code reports.
Schedule and grading
Workflow
- Select topic (report)
- Prepare material (present 5-10 min and discuss)
- Make presentation (20 min and questions)
- Write your text (2 pages and discuss)
- Publish your text (link)
Calendar
- Sep: 16, 23, 30 select
- Oct: 7, 14, 21, 28 talk
- Nov: 4, 11 talk, 18, 25 text
- Dec: 2 link, 9 fin
Insert your name and direct link to materials
| Date | Select | Talk | Text |
|---|---|---|---|
| 16nxt | Islamov, Strijov | ||
| 23sep | |||
| 30 | |||
| 7oct | x | ||
| 14 | |||
| 21 | |||
| 28 | |||
| 4nov | |||
| 11 | |||
| 18 | x | ||
| 25 | x |
Course page, and projects
- TODO Course page
- TODO Projects
The result links
- Bronstein, M. Temporal Graph Networks, Medium TDS
