Интеллектуальный анализ данных (О.Ю. Бахтеев, В.В. Стрижов)/Осень 2022

Материал из MachineLearning.

(Различия между версиями)
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'''Each tuesday 16:10 at the channel [http://m1p.org/go_zoom m1p.org/go_zoom]'''
'''Each Saturday 13:10 at the channel [http://m1p.org/go_zoom m1p.org/go_zoom]'''
{{Main|Численные методы обучения по прецедентам (практика, В.В. Стрижов)}}
{{Main|Численные методы обучения по прецедентам (практика, В.В. Стрижов)}}

Версия 08:18, 8 сентября 2022

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

  • [Sep] 16, 23, 30
  • [Oct] 7, 14, 21, 28
  • [Nov] 4, 11, 18, 25
  • [Dec] 2, 9
  1. Select topic (report)
  2. Prepare material (present 5-10 min and discuss)
  3. Make presentation (20 min and questions)
  4. Write your text (2 pages and discuss)
  5. Publish your text (link)

Course page, and projects

  • TODO Course page
  • TODO Projects

The result links

Topics to discuss

Examples and references

Личные инструменты