EFI Data Analytics for Physics

Session

Afternoon session

30 Oct 2017, 13:00

1. Introduction to pattern recognition algorithms and Machine Learning

Ben Nachman (Lawrence Berkeley National Lab. (US))

30/10/2017, 13:00

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. Advanced machine learning application in high energy physics

Ben Nachman (Lawrence Berkeley National Lab. (US))

30/10/2017, 15:00

4. Keras deep learning images

Mats Joakim Robert Olsson (University of Chicago (US))

30/10/2017, 15:45

9. Demo: Balancing a pole using "Reinforcement Learning"

Mats Joakim Robert Olsson (University of Chicago (US))

30/10/2017, 16:35

14. Run jobs on distributed computing

01/11/2017, 13:00

15. MVA and/or machine learning examples

01/11/2017, 13:20

16. Visualizations

01/11/2017, 13:50

17. Wrap up

01/11/2017, 14:10