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Second Machine Learning in High Energy Physics Summer School 2016

20–26 Jun 2016
Lund University
Europe/Copenhagen timezone

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Session

Lectures

20 Jun 2016, 10:20
Lundmarkssalen (Lund University)

Lundmarkssalen

Lund University

Lund University, Lund, Sweden

Conveners

Lectures: Day 1 lectures

  • Aleksei Rogozhnikov (Yandex School of Data Analysis (RU))

Lectures: Day 2 lectures

  • Aleksei Rogozhnikov (Yandex School of Data Analysis (RU))

Lectures: Day 3 lectures

  • Aleksei Rogozhnikov (Yandex School of Data Analysis (RU))

Lectures: Day 4 lectures

  • Tatiana Likhomanenko (National Research Centre Kurchatov Institute (RU))

Lectures: Deep learning

  • Alexander Panin (Yandex School of Data Analysis (RU))

Presentation materials

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  1. 6. Intro: General pipeline, ML at a glance, model evaluation
    20/06/2016, 10:20

    Featuring cross-validation and ROC AUC

    Go to contribution page
  2. 7. Metric ML algorithms
    20/06/2016, 12:00

    SVM, KNN, Linear regression

    Go to contribution page
  3. 10. Decision trees
    21/06/2016, 09:30
  4. 11. Ensembles
    21/06/2016, 11:10

    bagging & boosting

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  5. 14. Feature engineering, Dimensionality reduction
    22/06/2016, 09:30
  6. 15. Hyperparameters search
    22/06/2016, 11:10

    Featuring Gaussian processes

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  7. 18. Boosting reweighting and flatness
    23/06/2016, 09:30
  8. 22. Deep learning I
    Mr Alexander Panin (Yandex School of Data Analysis (RU))
    25/06/2016, 09:30
  9. 23. Deep learning II
    Mr Alexander Panin (Yandex School of Data Analysis (RU))
    25/06/2016, 11:10
  10. 19. Boosting reweighting and flatness - seminar
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