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

Материал из MachineLearning.

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(Новая: '''Each tuesday 16:10 at the channel [http://m1p.org/go_zoom m1p.org/go_zoom]''' {{Main|Численные методы обучения по прецедентам (практика, ...)
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==Examples and references==
==Examples and references==
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* [https://towardsdatascience.com/questions-96667b06af5#dee8 TDS guidelines]

Версия 08:02, 8 сентября 2022

Each tuesday 16:10 at the channel m1p.org/go_zoom

Основная статья: Численные методы обучения по прецедентам (практика, В.В. Стрижов)


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

  • [Sep] 6, 13, 20, 27~--- lab 1
  • [Oct] 4, 14, 18, 25~--- lab 2, 3
  • [Nov] 8, 15, 22, 29~--- lab 4
  • [Dec] 6, 13 exam

Topics to discuss

Examples and references

Источник — «http://machinelearning.ru/wiki/index.php?title=%D0%98%D0%BD%D1%82%D0%B5%D0%BB%D0%BB%D0%B5%D0%BA%D1%82%D1%83%D0%B0%D0%BB%D1%8C%D0%BD%D1%8B%D0%B9_%D0%B0%D0%BD%D0%B0%D0%BB%D0%B8%D0%B7_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D1%85_%28%D0%9E.%D0%AE._%D0%91%D0%B0%D1%85%D1%82%D0%B5%D0%B5%D0%B2%2C_%D0%92.%D0%92._%D0%A1%D1%82%D1%80%D0%B8%D0%B6%D0%BE%D0%B2%29/%D0%9E%D1%81%D0%B5%D0%BD%D1%8C_2022»
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