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Third Machine Learning in High Energy Physics Summer School 2017

17–23 Jul 2017
Reading
Europe/London timezone

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Session

Seminars

17 Jul 2017, 11:10
Reading University (Reading)

Reading University

Reading

Reading University, Reading, United Kingdom

Conveners

Seminars: Day 1 Seminars

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

Seminars: Day 1 Seminars

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

Seminars: Day 2 Seminars

  • There are no conveners in this block

Seminars: Day 2 seminrs

  • There are no conveners in this block

Seminars: Day 4 Seminars

  • There are no conveners in this block

Seminars: Day 4 Seminars

  • There are no conveners in this block

Seminars: Day 5 Seminars

  • There are no conveners in this block

Seminars: Day 6 Seminars

  • There are no conveners in this block

Presentation materials

There are no materials yet.

  1. 29. Seminar 1. Python data crunching: numpy, root_numpy, pandas (very short), matplotlib.
    Alexander Panin (Yandex School of Data Analysis (RU))
    17/07/2017, 11:10
  2. 31. Seminar 2. Matplotlib, Trees & Linear Models in SciKit Learn. Overfitting checks & prevention.
    Alexander Panin (Yandex School of Data Analysis (RU))
    17/07/2017, 15:50
  3. 32. Seminar 3. Ensembling: Adaboost, Stacking. Gradient Boosting.
    18/07/2017, 11:00
  4. 13. Seminar 4. Optimization of hyper-parameters, applications to challenge.
    18/07/2017, 15:30
  5. 37. Seminar 5. Computing gradient by hand. Tensorflow. Keras. Remote machine setup. Getting familiar with GPU.
    20/07/2017, 11:00
  6. 46. Seminar 6. Image recognition using convolutional neural networks.
    20/07/2017, 15:30
  7. 39. Seminar 7. PCA, Autoencoders (faces)
    21/07/2017, 15:30
  8. 41. Seminar 8 Generative Adversarial Networks (physics)
    22/07/2017, 11:00
  9. 8. Course technicalities, working environment
  10. 24. Deep learning III
    Mr Alexander Panin (Yandex School of Data Analysis (RU))
  11. 25. Deep learning IV
    Mr Alexander Panin (Yandex School of Data Analysis (RU))
  12. 27. Deep neural networks
    Alexander Panin (Yandex School of Data Analysis (RU))
  13. 16. Ensemble algorithms, dimensionality reduction

    Random forest, gradient boosting, PCA

    Go to contribution page
  14. 21. Feature engineering and selection
    Nikita Kazeev (Yandex School of Data Analysis (RU))

    Flatness boosting and reweighting

    Go to contribution page
  15. 17. Hyperparameters search
  16. 12. Model evaluation

    Overfitting, Cross-validation

    Go to contribution page
  17. 9. Python for data analysis; Probability density estimation

    numpy, root_numpy, pandas, matplotlib

    Go to contribution page
  18. 35. Seminar 6. Image recognition using convolutional neural networks.
  19. 20. Shallow neural networks
    Alexander Panin (Yandex School of Data Analysis (RU))
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