EFI Data Analytics for Physics

Oct 30, 2017, 9:00 AM → Nov 1, 2017, 5:00 PM America/Chicago

https://efi.uchicago.edu/content/efi-data-analytics-physics

For hands-on sessions participants will have access to personal JupyterLab instances. To get address of your instance please go to this address, select a free instance and add your name to it.

https://goo.gl/TTrbDt

You have full freedom on it, if you manage to destroy it ask for it to be recreated.

 

Monday, October 30

9:30 AM → 10:00 AM Coffee and tea

10:00 AM → 12:00 PM Intro session

10:00 AM Introduction and round table

Speaker: David Miller (University of Chicago (US))

Miller_Intro_30Oct2017.pdf

10:20 AM Discussion of projects for the workshop

Link to GitHub with various exercises

10:40 AM Integrative Cyberinfrastructure for the EFI

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

Slides

10:50 AM Brief introduction to modern data analysis environments

Speaker: Dr Benedikt Riedel (University of Chicago)

Brief Introduction to Modern Analysis Environments

11:10 AM Hands-on session with Python, Jupyter Notebooks, and ROOT

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.

Speaker: Giordon Holtsberg Stark (University of Chicago (US))

Tutorial

• 0 - Overview
• 1 - JuPyter Tutorial
• 2 - Python Tutorial
• 3 - NumPy Tutorial
• 4 - Plotting Basics

12:00 PM → 1:00 PM Lunch break

1:00 PM → 5:30 PM Afternoon session: Doing stuff

1:00 PM Introduction to pattern recognition algorithms and Machine Learning

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

Nachman_IntroMachineLearning.pdf

1:45 PM Hands-on: 1D optimal classifier, e.g. a Gaussian process classifier, compared with a simple Neural Network

Speakers: Ben Nachman (Lawrence Berkeley National Lab. (US)), Mats Joakim Robert Olsson (University of Chicago (US))

2:30 PM Coffee break

3:00 PM Advanced machine learning application in high energy physics

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

Nachman_AdvancedMachineLearning.pdf

3:45 PM Keras deep learning images

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

4:35 PM Demo: Balancing a pole using "Reinforcement Learning"

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

Tuesday, October 31

9:30 AM → 12:00 PM Morning session: Statistical Analysis Tools

9:30 AM Introduction to statistical analysis tools

Counting experiments: RooStats / HistFitter
Spectrum experiments: BumpHunter

Speaker: Maximilian J Swiatlowski (University of Chicago (US))

swiatlow.pdf

9:55 AM Hands-on with HistFitter for counting experiments

Speaker: Maximilian J Swiatlowski (University of Chicago (US))

10:20 AM Coffee Break

10:40 AM Data visualization with ROOT, D3, Bokeh, and HoloViews

Speaker: Teodora Szasz (University of Chicago Research Computing Center)

Presentation

12:00 PM → 1:00 PM Lunch break

1:00 PM → 6:00 PM Break for 50th anniversary UChicago-Fermilab Event

Wednesday, November 1

9:30 AM → 12:00 PM Morning session: Distributed computing

9:30 AM Introduction to distributed computing

Speaker: Lincoln Bryant (University of Chicago (US))

Slides

9:50 AM Hands-on session with OSG Connect

Speaker: Benedikt Riedel (University of Chicago)

10:20 AM Coffee break

10:45 AM Introduction to Elasticsearch

Speaker: Ilija Vukotic (University of Chicago (US))

Elasticsearch - what, why, how

11:05 AM Hands on: using Elasticsearch for ML

Speaker: Ilija Vukotic (University of Chicago (US))

12:00 PM → 1:00 PM Lunch break

1:00 PM → 3:30 PM Afternoon session: Synthesis of previous work

1:00 PM Run jobs on distributed computing

1:20 PM MVA and/or machine learning examples

1:50 PM Visualizations

2:10 PM Wrap up