A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
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Updated
Jun 2, 2024
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
A Python package to assess and improve fairness of machine learning models.
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.
The Python Risk Identification Tool for generative AI (PyRIT) is an open access automation framework to empower security professionals and machine learning engineers to proactively find risks in their generative AI systems.
🐢 Open-Source Evaluation & Testing for LLMs and ML models
moDel Agnostic Language for Exploration and eXplanation
A toolkit that streamlines and automates the generation of model cards
Step-by-Step tutorial that teaches you how to use Azure Safety Content - the prebuilt AI service that helps ensure that content sent to user is filtered to safeguard them from risky or undesirable outcomes
💡 Adversarial attacks on explanations and how to defend them
Deliver safe & effective language models
Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
A "Responsible AI For Developers" hub to help developer audiences (students, entrepreneurs and professionals) discover workshop, events and resources that can help them learn and use Responsible AI concepts and resources effectively in their own projects.
A detailed summary of "Designing Machine Learning Systems" by Chip Huyen. This book gives you and end-to-end view of all the steps required to build AND OPERATE ML products in production. It is a must-read for ML practitioners and Software Engineers Transitioning into ML.
Carefully curated list of awesome data science resources.
A collection of news articles, books, and papers on Responsible AI cases. The purpose is to study these cases and learn from them to avoid repeating the failures of the past.
[ICCV 2023 Oral, Best Paper Finalist] ITI-GEN: Inclusive Text-to-Image Generation
A curated list of awesome academic research, books, code of ethics, data sets, institutes, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible AI, Trustworthy AI, and Human-Centered AI.
Référentiel d'évaluation data science responsable et de confiance
Taught by AI genius Andrew NG, this course entails the cutting edge topics such as, How generative AI works including what it can and can't do, Common uses cases such as Reading, Writing, and Chatting, Life Cycle of GenAI projects, Advanced Technology options such as RAG, Fine tunning, and Pre-Training, Implications of GenAI on business & Society.
Oracle Guardian AI Open Source Project is a library consisting of tools to assess fairness/bias and privacy of machine learning models and data sets.
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