Skip to content

Latest commit

 

History

History
9 lines (7 loc) · 916 Bytes

README.md

File metadata and controls

9 lines (7 loc) · 916 Bytes

This repository is intended to create a series of notebooks that illustrate the FAIR principles in the context of High Energy Physics Data and AI models. The FAIR acronym stands for Findable, Accessible, Interoperable, and Reusable- benchmarking a set of desired qualities that ensure transparent and objective scientific data management.

List of Notebooks:

  • 01-Intro2FAIR.ipynb: Introduces the FAIR principles and a set metrics used to evaluate FAIRness of datasets
  • 02-FAIRCheck-MNIST.ipynb: Explores the MNIST dataset and its FAIRness using the metrics introduced in the previous notebook
  • 03-FAIRCheck-CDMS.ipynb: Explores the superCDMS dataset and its FAIRness
  • 04-CDMS-LR.ipynb: Explores linear regression along with Ridge and Lasso Regularizations and preservation of these models
  • 05-CDMS-PCA.ipynb: Explores Principal Component Analysis based linear regression