EFI Data Analytics for Physics

Contribution List

5. Introduction and round table

David Miller (University of Chicago (US))

30/10/2017, 10:00

Intro session

6. Discussion of projects for the workshop

30/10/2017, 10:20

Intro session

18. Integrative Cyberinfrastructure for the EFI

Robert William Gardner Jr (University of Chicago (US))

30/10/2017, 10:40

Intro session

7. Brief introduction to modern data analysis environments

Dr Benedikt Riedel (University of Chicago)

30/10/2017, 10:50

Intro session

8. Hands-on session with Python, Jupyter Notebooks, and ROOT

Giordon Holtsberg Stark (University of Chicago (US))

30/10/2017, 11:10

Intro session

Make sure to sign up for a particular JupyterLab instance.

Then navigate to that instance by typing the URL into your browser. The password for JupyterLab is written on the board in the room.

1. Introduction to pattern recognition algorithms and Machine Learning

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

30/10/2017, 13:00

Afternoon session

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

Afternoon session

3. Advanced machine learning application in high energy physics

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

30/10/2017, 15:00

Afternoon session

4. Keras deep learning images

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

30/10/2017, 15:45

Afternoon session

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

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

30/10/2017, 16:35

Afternoon session

19. Introduction to statistical analysis tools

Maximilian J Swiatlowski (University of Chicago (US))

31/10/2017, 09:30

Morning session

Counting experiments: RooStats / HistFitter
Spectrum experiments: BumpHunter

20. Hands-on with HistFitter for counting experiments

Maximilian J Swiatlowski (University of Chicago (US))

31/10/2017, 09:55

Morning session

21. Data visualization with ROOT, D3, Bokeh, and HoloViews

Teodora Szasz (University of Chicago Research Computing Center)

31/10/2017, 10:40

Morning session

10. Introduction to distributed computing

Lincoln Bryant (University of Chicago (US))

01/11/2017, 09:30

Morning session

11. Hands-on session with OSG Connect

Benedikt Riedel (University of Chicago)

01/11/2017, 09:50

Morning session

12. Introduction to Elasticsearch

Ilija Vukotic (University of Chicago (US))

01/11/2017, 10:45

Morning session

13. Hands on: using Elasticsearch for ML

Ilija Vukotic (University of Chicago (US))

01/11/2017, 11:05

Morning session

14. Run jobs on distributed computing

01/11/2017, 13:00

Afternoon session

15. MVA and/or machine learning examples

01/11/2017, 13:20

Afternoon session

16. Visualizations

01/11/2017, 13:50

Afternoon session

17. Wrap up

01/11/2017, 14:10

Afternoon session

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