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EFI Data Analytics for Physics

30 October 2017 to 1 November 2017
America/Chicago timezone

Session

Afternoon session

30 Oct 2017, 13:00

Presentation materials

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  1. 1. Introduction to pattern recognition algorithms and Machine Learning
    Ben Nachman (Lawrence Berkeley National Lab. (US))
    30/10/2017, 13:00
  2. 2. Hands-on: 1D optimal classifier, e.g. a Gaussian process classifier, compared with a simple Neural Network
    Ben Nachman (Lawrence Berkeley National Lab. (US)), Mats Joakim Robert Olsson (University of Chicago (US))
    30/10/2017, 13:45
  3. 3. Advanced machine learning application in high energy physics
    Ben Nachman (Lawrence Berkeley National Lab. (US))
    30/10/2017, 15:00
  4. 4. Keras deep learning images
    Mats Joakim Robert Olsson (University of Chicago (US))
    30/10/2017, 15:45
  5. 9. Demo: Balancing a pole using "Reinforcement Learning"
    Mats Joakim Robert Olsson (University of Chicago (US))
    30/10/2017, 16:35
  6. 14. Run jobs on distributed computing
    01/11/2017, 13:00
  7. 15. MVA and/or machine learning examples
    01/11/2017, 13:20
  8. 16. Visualizations
    01/11/2017, 13:50
  9. 17. Wrap up
    01/11/2017, 14:10
Building timetable...