Difference between revisions of "AI tutorials"
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Revision as of 12:44, 23 January 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
References
Workshop Software
Agenda
Feb 18
Feb 19
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 | Yes |
| 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 |
