IBM/UQ360
Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.
This toolkit helps data science practitioners understand the reliability of their machine learning model predictions. You feed in your existing machine learning model and data, and it provides estimates of prediction uncertainty, allowing you to communicate how confident your model is. This is ideal for data scientists who need to ensure transparency and trust in their AI systems.
267 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to quantify, evaluate, and communicate the uncertainty associated with your machine learning model's predictions to stakeholders.
Not ideal if you are looking for a tool to build machine learning models from scratch, as this focuses on evaluating existing model predictions.
Stars
267
Forks
64
Language
Python
License
Apache-2.0
Last pushed
Sep 17, 2025
Commits (30d)
0
Dependencies
16
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