Difference between revisions of "AI tutorials"
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* 09:00 Welcome (5min) | * 09:00 Welcome (5min) | ||
− | * 09:05 Brief introduction to Machine and Deep Learning (1h35) | + | * 09:05 Brief introduction to Machine and Deep Learning (Daniel Lersch - 1h35) |
* 10:40 Break (20 min) | * 10:40 Break (20 min) | ||
* 11:00 Notebook setup (15min) | * 11:00 Notebook setup (15min) | ||
− | * 11:15 Data preparation and feature engineering (1h15) | + | * 11:15 Data preparation and feature engineering (Anupam Siwakoti - 1h15) |
* 12:30 Lunch (1 h) | * 12:30 Lunch (1 h) | ||
− | * 13:30 Setting up a model and training it (1h15) | + | * 13:30 Setting up a model and training it (Zach Baldwin - 1h15) |
− | * 14:45 Final performance evaluation (1h15) | + | * 14:45 Final performance evaluation (Zach Baldwin - 1h15) |
* 16:00 Break (20min) | * 16:00 Break (20min) | ||
− | * 16:30 HYDRA (45min) | + | * 16:30 HYDRA (Torri Jeske - 45min) |
<b>Feb 19</b> | <b>Feb 19</b> | ||
− | * 09: | + | * 09:30 TMVA (Andrew Schick - 1h) |
− | * 10: | + | * 10:30 Break (20min) |
− | + | * 10:50 Graph Neural Network (Ahmed Mohammed - 45min) | |
− | * | + | |
| |
Revision as of 14:39, 16 February 2025
Contents
Purpose
The overall topic is: „Best practice for AI in nuclear physics applications“. We wish to cover the following items via plenary talks and/or interactive tutorials:
- Feature engineering --> Feature normalization, correlation coefficients, feature selection, etc.
- Overfitting --> Dropout layers, weight regularization, etc.
- Performance evaluation --> ROC-Curve, confusion matrix, accuracy, loss curves,...
- Visualization --> How to properly present the performance of a model ? What are "good" diagnostic plots ?
- Model deployment --> How to use a model within the GlueX analysis software
- Data fed into models --> What data sets are used ? Numerical, vs. Images, raw data vs. clean data,...
- Tools made available by the data science department
- Optional, depending on time: HPO --> Tune the parameters of your model
- Optional, depending on time: Bookkeeping of models via MLFlow
Location and Time
The workshop will take place at:
DATES: February 18 (all day) - 19 (morning only), 2025
LOCATION: CEBAF Center F113
Remote Participation
Zoom link can be found below:
References
- Google colab: https://colab.google/
Workshop Software
Agenda
AI Tutorials
Feb 18
- 09:00 Welcome (5min)
- 09:05 Brief introduction to Machine and Deep Learning (Daniel Lersch - 1h35)
- 10:40 Break (20 min)
- 11:00 Notebook setup (15min)
- 11:15 Data preparation and feature engineering (Anupam Siwakoti - 1h15)
- 12:30 Lunch (1 h)
- 13:30 Setting up a model and training it (Zach Baldwin - 1h15)
- 14:45 Final performance evaluation (Zach Baldwin - 1h15)
- 16:00 Break (20min)
- 16:30 HYDRA (Torri Jeske - 45min)
Feb 19
- 09:30 TMVA (Andrew Schick - 1h)
- 10:30 Break (20min)
- 10:50 Graph Neural Network (Ahmed Mohammed - 45min)
Registration
Please add your name to the list of attendees below. No formal registration or registration fee is required.
Name | Home Institution | Level | Participate at JLab | |
---|---|---|---|---|
ig | JLab | Staff | Yes | |
Daniel | JLab | Staff | Yes | |
Gyang | Virginia Tech | Student | No | |
Karthik | William and Mary | Postdoc | No | |
Zachary Baldwin | Carnegie Mellon University | Graduate Student | Yes | |
Nizar Septian | Florida State University | Student | Yes | |
Alex Austregesilo | JLab | Staff | Yes | |
Drew Smith | JLab | Postdoc | Yes | |
Sean Dobbs | FSU | Faculty | Yes | |
Will Imoehl | Carnegie Mellon University | Postdoc | No | |
Farah Afzal | Ruhr University Bochum | Faculty | Yes | |
Peter Hurck | Glasgow | Faculty | Yes | |
Lawrence Ng | JLab | Postdoc | Yes | |
Albert Fabrizi | University of Mass. Amherst | Graduate Student | Yes | |
Shannen Graham-Howard | University of Mass. Amherst | Graduate Student | Yes | |
Jiawei Guo | Carnegie Mellon University | Graduate Student | Yes | |
Boris Grube | JLab | Staff | Yes | |
Churamani Paudel | FIU | Postdoc | No | |
Vitor Shen | Ruhr University Bochum | Graduate Student | No | |
Kevin Saldaña | Indiana University | Graduate Student | Yes |