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
☆445Aug 21, 2024Updated last year
Alternatives and similar repositories for explainx
Users that are interested in explainx are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- XAI - An eXplainability toolbox for machine learning☆1,233Nov 29, 2025Updated 5 months ago
- A collection of research materials on explainable AI/ML☆1,632Mar 7, 2026Updated last month
- Interpretability and explainability of data and machine learning models☆1,775Mar 18, 2026Updated last month
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆854May 31, 2022Updated 3 years ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,508Jul 13, 2025Updated 9 months ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- A curated list of awesome responsible machine learning resources.☆4,016Mar 16, 2026Updated last month
- Fit interpretable models. Explain blackbox machine learning.☆6,840Updated this week
- Algorithms for explaining machine learning models☆2,626Oct 17, 2025Updated 6 months ago
- moDel Agnostic Language for Exploration and eXplanation☆1,466Jan 20, 2026Updated 3 months ago
- A Python library for Interpretable Machine Learning in Text Classification using the SS3 model, with easy-to-use visualization tools for …☆348Oct 16, 2025Updated 6 months ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,585Apr 13, 2026Updated 2 weeks ago
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.☆2,483Feb 11, 2026Updated 2 months ago
- Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upo…☆546Jan 30, 2025Updated last year
- 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models☆3,208Updated this week
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- 📍 Interactive Studio for Explanatory Model Analysis☆332Aug 31, 2023Updated 2 years ago
- FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)☆72Oct 20, 2021Updated 4 years ago
- Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, …☆681Jun 17, 2024Updated last year
- Human-explainable AI.☆531Feb 10, 2026Updated 2 months ago
- Feature engineering and selection open-source Python library compatible with sklearn.☆2,233Mar 28, 2026Updated last month
- Papers and code of Explainable AI esp. w.r.t. Image classificiation☆226Jun 28, 2022Updated 3 years ago
- Library for statistical testing and comparison of algorithm results☆18Mar 30, 2026Updated last month
- For calculating global feature importance using Shapley values.☆287Updated this week
- A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in …☆432Feb 5, 2024Updated 2 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Model interpretability and understanding for PyTorch☆5,614Updated this week
- Leave One Feature Out Importance☆866Feb 14, 2025Updated last year
- Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ra…☆767Aug 20, 2024Updated last year
- Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world d…☆442Feb 7, 2025Updated last year
- machine learning with logical rules in Python☆659Jan 31, 2024Updated 2 years ago
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆652Feb 19, 2024Updated 2 years ago
- A unified wrapper for various ML frameworks - to have one uniform scikit-learn format for predict and predict_proba functions.☆50Mar 17, 2026Updated last month
- Extra blocks for scikit-learn pipelines.☆1,392Apr 21, 2026Updated last week
- A game theoretic approach to explain the output of any machine learning model.☆25,355Updated this week
- Proton VPN Special Offer - Get 70% off • AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- Flexible tool for bias detection, visualization, and mitigation☆85Oct 31, 2025Updated 6 months ago
- A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning☆20,461Updated this week
- Python implementation of the rulefit algorithm☆445Oct 8, 2023Updated 2 years ago
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆2,776Apr 8, 2026Updated 3 weeks ago
- H2O.ai Machine Learning Interpretability Resources☆492Dec 12, 2020Updated 5 years ago
- The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic …☆3,651Apr 15, 2026Updated 2 weeks ago
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆328Apr 20, 2025Updated last year