microsoft / responsible-ai-toolbox
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
☆1,463Updated 2 weeks ago
Alternatives and similar repositories for responsible-ai-toolbox:
Users that are interested in responsible-ai-toolbox are comparing it to the libraries listed below
- A Python package to assess and improve fairness of machine learning models.☆2,008Updated this week
- Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world d…☆424Updated last week
- Bias Auditing & Fair ML Toolkit☆706Updated 5 months ago
- Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.☆537Updated 8 months ago
- Source code/webpage/demos for the What-If Tool☆935Updated 5 months ago
- Official community-driven Azure Machine Learning examples, tested with GitHub Actions.☆1,826Updated this week
- A toolkit that streamlines and automates the generation of model cards☆428Updated last year
- MLOps examples☆1,892Updated 6 months ago
- Interpretability and explainability of data and machine learning models☆1,655Updated 7 months ago
- Tensorflow's Fairness Evaluation and Visualization Toolkit☆347Updated 3 weeks ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,383Updated 2 months ago
- Project for open sourcing research efforts on Backward Compatibility in Machine Learning☆73Updated last year
- A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitig…☆2,520Updated 2 months ago
- Algorithms for explaining machine learning models☆2,447Updated 2 months ago
- A library that implements fairness-aware machine learning algorithms☆125Updated 4 years ago
- Curated list of open source tooling for data-centric AI on unstructured data.☆709Updated last year
- MLOps using Azure ML Services and Azure DevOps☆1,225Updated last year
- Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML va…☆3,709Updated this week
- This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and b…☆1,300Updated last month
- MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integra…☆1,486Updated this week
- A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.☆4,047Updated this week
- 🔍 LangKit: An open-source toolkit for monitoring Large Language Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring sa…☆877Updated 2 months ago
- The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to s…☆691Updated last month
- nannyml: post-deployment data science in python☆2,022Updated last month
- Algorithms for outlier, adversarial and drift detection☆2,302Updated last month
- Repo to hold examples of responsible model assessment for a variety of different verticals such as healthcare and financial services☆62Updated last year
- ZenML 🙏: The bridge between ML and Ops. https://zenml.io.☆4,418Updated this week
- Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.☆1,325Updated last year
- Source code accompanying O'Reilly book: Machine Learning Design Patterns☆1,936Updated 3 years ago
- OmniXAI: A Library for eXplainable AI☆898Updated 6 months ago