Trusted-AI / AIX360
Interpretability and explainability of data and machine learning models
☆1,652Updated 6 months ago
Alternatives and similar repositories for AIX360:
Users that are interested in AIX360 are comparing it to the libraries listed below
- A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitig…☆2,498Updated last month
- Algorithms for explaining machine learning models☆2,429Updated last month
- XAI - An eXplainability toolbox for machine learning☆1,146Updated 3 years ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,373Updated last month
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆819Updated 2 years ago
- ☆910Updated last year
- Code for "High-Precision Model-Agnostic Explanations" paper☆799Updated 2 years ago
- Source code/webpage/demos for the What-If Tool☆931Updated 4 months ago
- Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world d…☆424Updated 7 months ago
- OmniXAI: A Library for eXplainable AI☆892Updated 5 months ago
- Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty i…☆257Updated 4 months ago
- Library for Semi-Automated Data Science☆333Updated 4 months ago
- Bias Auditing & Fair ML Toolkit☆703Updated 4 months ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆573Updated 2 months ago
- A Python package to assess and improve fairness of machine learning models.☆1,988Updated this week
- Algorithms for outlier, adversarial and drift detection☆2,284Updated last month
- H2O.ai Machine Learning Interpretability Resources☆483Updated 4 years ago
- Code for the TCAV ML interpretability project☆634Updated 5 months ago
- Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, …☆673Updated 7 months ago
- A collection of research materials on explainable AI/ML☆1,442Updated 2 months ago
- Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are look…☆422Updated 4 months ago
- CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms☆286Updated last year
- python partial dependence plot toolbox☆849Updated 4 months ago
- A curated list of awesome responsible machine learning resources.☆3,703Updated last week
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,416Updated last week
- A toolkit that streamlines and automates the generation of model cards☆427Updated last year
- Tensorflow's Fairness Evaluation and Visualization Toolkit☆345Updated this week
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆237Updated 5 months ago
- A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also in…☆742Updated 4 years ago
- Attributing predictions made by the Inception network using the Integrated Gradients method☆607Updated 2 years ago