H2O.ai Machine Learning Interpretability Resources
☆492Dec 12, 2020Updated 5 years ago
Alternatives and similar repositories for mli-resources
Users that are interested in mli-resources are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, …☆681Jun 17, 2024Updated last year
- A curated list of awesome responsible machine learning resources.☆4,008Mar 16, 2026Updated last month
- Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!☆29Jul 13, 2019Updated 6 years ago
- ☆917Mar 19, 2023Updated 3 years ago
- Library for integrated use of H2O with Hyperopt☆13Apr 8, 2024Updated 2 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- moDel Agnostic Language for Exploration and eXplanation☆1,463Jan 20, 2026Updated 2 months ago
- Fit interpretable models. Explain blackbox machine learning.☆6,830Updated this week
- Guidelines for the responsible use of explainable AI and machine learning.☆17Jan 30, 2023Updated 3 years ago
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆853May 31, 2022Updated 3 years ago
- XAI - An eXplainability toolbox for machine learning☆1,232Nov 29, 2025Updated 4 months ago
- H2OAI Driverless AI Code Samples and Tutorials☆38Oct 24, 2024Updated last year
- Materials for GWU DNSC 6279 and DNSC 6290.☆241May 27, 2025Updated 10 months ago
- ☆38May 7, 2025Updated 11 months ago
- Code for "High-Precision Model-Agnostic Explanations" paper☆813Jul 19, 2022Updated 3 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Python implementation of the rulefit algorithm☆444Oct 8, 2023Updated 2 years ago
- Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/☆27Jun 17, 2024Updated last year
- This is a repo for all the tutorials put out by H2O.ai. This includes learning paths for Driverless AI, H2O-3, Sparkling Water and more..…☆135Aug 2, 2024Updated last year
- Lime: Explaining the predictions of any machine learning classifier☆12,119Jul 25, 2024Updated last year
- All about explainable AI, algorithmic fairness and more☆110Sep 24, 2023Updated 2 years ago
- Public experimental example code for the ProPublic recidivism data-based experiments for the upcoming Interpretable Active Learning Paper☆10Dec 18, 2017Updated 8 years ago
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆2,777Apr 8, 2026Updated last week
- Book about interpretable machine learning☆5,273Jan 15, 2026Updated 3 months ago
- LOcal Rule-based Exlanations☆53Nov 28, 2023Updated 2 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Tutorials and training material for the H2O Machine Learning Platform☆1,503Oct 24, 2024Updated last year
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,507Jul 13, 2025Updated 9 months ago
- Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)☆84Nov 30, 2023Updated 2 years ago
- ☆761Jul 18, 2023Updated 2 years ago
- Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models☆490Aug 11, 2017Updated 8 years ago
- Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world d…☆442Feb 7, 2025Updated last year
- Materials for Machine Learning with H2O Open Platform at ODSC Masterclass Summit 2017☆12Mar 2, 2017Updated 9 years ago
- ☆366May 10, 2021Updated 4 years ago
- DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanatio…☆691Feb 21, 2023Updated 3 years ago
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- Model Agnostics breakDown plots☆104Mar 12, 2024Updated 2 years ago
- Research code for auditing and exploring black box machine-learning models.☆132May 24, 2023Updated 2 years ago
- Local Interpretable Model-Agnostic Explanations (R port of original Python package)☆492Dec 11, 2025Updated 4 months ago
- Presentations from H2O meetups & conferences by the H2O.ai team☆406Oct 29, 2025Updated 5 months ago
- Visual analysis and diagnostic tools to facilitate machine learning model selection.☆4,399Feb 19, 2025Updated last year
- A game theoretic approach to explain the output of any machine learning model.☆25,286Updated this week
- A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.☆99Jul 18, 2022Updated 3 years ago