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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

Seminars

20 Jun 2016, 14:35
Lundmarkssalen (Lund University)

Lundmarkssalen

Lund University

Lund University, Lund, Sweden

Conveners

Seminars: Day 1 seminars

  • Nikita Kazeev (Yandex School of Data Analysis (RU))

Seminars: Day 2 seminrs

  • Nikita Kazeev (Yandex School of Data Analysis (RU))

Seminars: Day 3 seminars

  • Nikita Kazeev (Yandex School of Data Analysis (RU))

Seminars: Day 4 seminars

  • There are no conveners in this block

Seminars: Deep learning

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

Seminars: Boosting reweighting and flatness - seminar

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

Presentation materials

There are no materials yet.

  1. 8. Course technicalities, working environment
    20/06/2016, 14:35
  2. 9. Python for data analysis; Probability density estimation
    20/06/2016, 16:15

    numpy, root_numpy, pandas, matplotlib

    Go to contribution page
  3. 12. Model evaluation
    21/06/2016, 13:30

    Overfitting, Cross-validation

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  4. 13. sklearn, simple algorithms
    21/06/2016, 15:10
  5. 16. Ensemble algorithms, dimensionality reduction
    22/06/2016, 13:30

    Random forest, gradient boosting, PCA

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  6. 21. Feature engineering and selection
    Nikita Kazeev (Yandex School of Data Analysis (RU))
    23/06/2016, 14:00

    Flatness boosting and reweighting

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  7. 20. Shallow neural networks
    Alexander Panin (Yandex School of Data Analysis (RU))
    23/06/2016, 15:40
  8. 27. Deep neural networks
    Alexander Panin (Yandex School of Data Analysis (RU))
    23/06/2016, 17:20
  9. 24. Deep learning III
    Mr Alexander Panin (Yandex School of Data Analysis (RU))
    25/06/2016, 13:30
  10. 25. Deep learning IV
    Mr Alexander Panin (Yandex School of Data Analysis (RU))
    25/06/2016, 15:10
  11. 17. Hyperparameters search
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