jphall663 / awesome-machine-learning-interpretabilityLinks
A curated list of awesome responsible machine learning resources.
☆3,942Updated 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:
- ☆919Updated 2 years ago
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆842Updated 3 years ago
- A collection of research materials on explainable AI/ML☆1,591Updated last week
- XAI - An eXplainability toolbox for machine learning☆1,211Updated 2 weeks ago
- Algorithms for explaining machine learning models☆2,600Updated 2 months ago
- Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, …☆679Updated last year
- Interpretability and explainability of data and machine learning models☆1,749Updated 9 months ago
- Fit interpretable models. Explain blackbox machine learning.☆6,740Updated this week
- H2O.ai Machine Learning Interpretability Resources☆491Updated 5 years ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,477Updated 5 months ago
- Code for "High-Precision Model-Agnostic Explanations" paper☆812Updated 3 years ago
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆2,773Updated 7 months ago
- This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and b…☆1,389Updated last month
- Book about interpretable machine learning☆5,157Updated 8 months ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,555Updated 3 weeks ago
- A curated list of gradient boosting research papers with implementations.☆1,035Updated last year
- Visual analysis and diagnostic tools to facilitate machine learning model selection.☆4,382Updated 9 months ago
- moDel Agnostic Language for Exploration and eXplanation☆1,451Updated last month
- Model interpretability and understanding for PyTorch☆5,485Updated 2 weeks ago
- Curating a list of AutoML-related research, tools, projects and other resources☆907Updated 3 months ago
- Lime: Explaining the predictions of any machine learning classifier☆12,072Updated last year
- PMLB: A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms.☆850Updated 9 months ago
- Bias Auditing & Fair ML Toolkit☆742Updated last week
- A curated list of articles that cover the software engineering best practices for building machine learning applications.☆1,329Updated last year
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.☆2,460Updated 4 months ago
- Source code/webpage/demos for the What-If Tool☆982Updated 2 weeks ago
- A Python package to assess and improve fairness of machine learning models.☆2,175Updated 2 weeks ago
- A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitig…☆2,722Updated last month
- A python library for decision tree visualization and model interpretation.☆3,111Updated last week
- OmniXAI: A Library for eXplainable AI☆959Updated last year