Interpretability

shapJupyter Notebook

A unified Python library for explaining any machine learning model's predictions using Shapley values from game theory.

Awesome Production Machine Learning

A curated list of awesome open-source libraries for deploying, monitoring, versioning, and scaling production machine learning systems.

privacy-preserving ML

A curated list of awesome open-source libraries for deploying, monitoring, versioning, and scaling production machine learning systems.

pytorch-grad-camPython

A PyTorch library providing state-of-the-art methods for generating visual explanations (Class Activation Maps) for computer vision models.

InterpretMLC++

An open-source Python package for training interpretable glassbox models and explaining blackbox machine learning systems.

lucidJupyter Notebook

A collection of infrastructure and tools for research in neural network interpretability and visualization.

Awesome Machine Learning Interpretability

A curated list of practical resources for responsible machine learning, covering interpretability, governance, safety, and ethics.

shapashJupyter Notebook

A Python library that makes machine learning models interpretable and transparent through user-friendly visualizations and a web application.

StellarGraphPython

A Python library for machine learning on graphs and networks, offering state-of-the-art algorithms for tasks like node classification and link prediction.

AlibiPython

A Python library for explaining machine learning models using black-box, white-box, local, and global interpretation methods.

Awesome Decision Tree PapersPython

A curated collection of research papers on decision, classification, and regression trees with implementations from top ML conferences.

PenzaiPython

A JAX research toolkit for building, editing, and visualizing neural networks as legible, functional pytree data structures.

Awesome Explainable AIMarkdown

A curated collection of research papers, books, courses, and Python libraries for explainable AI (XAI) and machine learning interpretability.

imodelsJupyter Notebook

A Python package for concise, transparent, and accurate predictive modeling with sklearn-compatible interpretable models.