Contributor
Anjishnu Mukherjee

Tutorials for Working with Interpretable and Explainable AI with 🔥LIT


Mentors
Ryan Mullins
Organization
Responsible AI and Human Centred Technology
Technologies
python, javascript, Technical writing
Topics
machine learning, ai, Fairness, Robustness, Interpretability
This project focuses on providing easy-to-understand walk-throughs of standard workflows for analyzing models using LIT and also providing in-depth how-tos for using and building on top of some of the LIT modules which are relevant for these workflows. Providing this content in the form of tutorials and code contributions over the summer, I hope to increase the accessibility to the tool for different types of users.