{"repo":"IBM/UQ360","free":true,"listed":false,"github":"https://github.com/IBM/UQ360","clone":"git clone https://github.com/IBM/UQ360.git","description":"Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.","language":"Python","stars":269,"topics":["uncertainty-quantification","metrics","uncertainty-estimates","machine-learning","artificial-intelligence","trusted-ai","uncertainty","bayesianneuralnetwork","calibration"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"UQ360 The Uncertainty Quantification 360 (UQ360) is an open-source toolkit with a Python package to provide data science practitioners and developers access to state-of-the-art algorithms, to streamline the process of estimating, evaluating, improving, and communicating uncertainty of machine learning models as common practices for AI transparency. The UQ360 interactive experience provides a gentle introduction to the concepts and capabilities by walking through an example use case. The tutorials and example notebooks offer a deeper, data scientist-oriented introduction. The complete API is also available. We have developed the package with extensibility in mind. This library is still in development. We encourage the contribution of your uncertainty estimation algorithms, metrics and applications. To get started as a contributor, please join the #uq360-users or #uq360-developers channel of the AIF360 Community on Slack by requesting an invitation here. Resources - Introduction to Uncertainty Quantification 360. - Demo House Price Prediction Model. - List of Algorithms supported. - List of Metrics supported. - Guidance on Choosing UQ Algorithms and Metrics. - Guidance on Communicating Uncertainty. - Glossary of UQ Terms. - Read our papers. - Complete list of tutorials. - Join the Slack Community. Example Use-cases Meta-models Use of meta-models to augment sklearn's gradient boosted regressor with prediction interval. See detailed example here. UQ360 metrics for model selection","default_branch":null,"files":null,"tree":[],"storefront":"/r/IBM","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/IBM/UQ360/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}