25DaysInMachineLearning

Fit interpretable models. Explain blackbox machine learning.

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

XAI - An eXplainability toolbox for machine learning

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

Curated list of open source tooling for data-centric AI on unstructured data.

Notes for Deep Learning Specialization Courses led by Andrew Ng.

Code to create Stylized-ImageNet, a stylized version of standard ImageNet (ICLR 2019 Oral)

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Kernels for machine learning problems

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms8909@nyu.edu