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

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

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.