Open Source AI Tools

Google's differential privacy libraries.

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

A library for debugging/inspecting machine learning classifiers and explaining their predictions

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Algorithms for explaining machine learning models

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

A Python package to assess and improve fairness of machine learning models.

Library for training machine learning models with privacy for training data

Interpretability and explainability of data and 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.