jphall663 / awesome-machine-learning-interpretabilityLinks
A curated list of awesome responsible machine learning resources.
☆3,967Updated 2 weeks ago
Alternatives and similar repositories for awesome-machine-learning-interpretability
Users that are interested in awesome-machine-learning-interpretability are comparing it to the libraries listed below
Sorting:
- A collection of research materials on explainable AI/ML☆1,605Updated last month
- ☆916Updated 2 years ago
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆845Updated 3 years ago
- XAI - An eXplainability toolbox for machine learning☆1,219Updated last month
- Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, …☆680Updated last year
- Fit interpretable models. Explain blackbox machine learning.☆6,768Updated 2 weeks ago
- Algorithms for explaining machine learning models☆2,607Updated 3 months ago
- H2O.ai Machine Learning Interpretability Resources☆490Updated 5 years ago
- This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and b…☆1,395Updated this week
- Interpretability and explainability of data and machine learning models☆1,756Updated 11 months ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,486Updated 6 months ago
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆2,772Updated 2 weeks ago
- moDel Agnostic Language for Exploration and eXplanation☆1,455Updated last week
- Code for "High-Precision Model-Agnostic Explanations" paper☆813Updated 3 years ago
- Book about interpretable machine learning☆5,205Updated last week
- A curated list of gradient boosting research papers with implementations.☆1,038Updated 3 weeks ago
- A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning☆20,031Updated 2 weeks ago
- Visual analysis and diagnostic tools to facilitate machine learning model selection.☆4,395Updated 11 months ago
- Model interpretability and understanding for PyTorch☆5,535Updated this week
- A guideline for building practical production-level deep learning systems to be deployed in real world applications.☆4,599Updated 7 months ago
- python partial dependence plot toolbox☆861Updated last year
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.☆2,469Updated 5 months ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,566Updated 2 months ago
- A Python package to assess and improve fairness of machine learning models.☆2,196Updated this week
- ☆620Updated 2 years ago
- Bias Auditing & Fair ML Toolkit☆746Updated last week
- A curated list of articles that cover the software engineering best practices for building machine learning applications.☆1,336Updated last year
- A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also in…☆760Updated 5 years ago
- Curating a list of AutoML-related research, tools, projects and other resources☆910Updated 5 months ago
- A library of extension and helper modules for Python's data analysis and machine learning libraries.☆5,094Updated this week