A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

🐢 Open-Source Evaluation & Testing library for LLM Agents

The Python Risk Identification Tool for generative AI (PyRIT) is an open source framework built to empower security professionals and engineers to proactively identify risks in generative AI systems.

Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have this answer in less than 120 seconds.

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.

moDel Agnostic Language for Exploration and eXplanation

RAG Time: A 5-week Learning Journey to Mastering RAG

A resource repository for machine unlearning in large language models

Deliver safe & effective language models

A toolkit that streamlines and automates the generation of model cards

The testing platform for AI teams. Bring engineers, PMs, and domain experts together to generate tests, simulate (adversarial) conversations, and trace every failure to its root cause.

💡 Adversarial attacks on explanations and how to defend them

FIBO is a SOTA, first open-source, JSON-native text-to-image model built for controllable, predictable, and legally safe image generation.

The IQ Series is a hands-on learning experience for Microsoft IQ: Microsoft's unified intelligence layer for the enterprise, spanning Foundry IQ, Work IQ, and Fabric IQ. The series includes video episodes, Jupyter notebooks, and Azure deployment templates.

Synthetic fraud graph generator for benchmarking graph-based fraud detection models in financial services.

LangFair is a Python library for conducting use-case level LLM bias and fairness assessments

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.

Simpack Pro 2.0: AI Investment Intelligence Platform 2026