PROCEEDINGS OF THE 5TH JOINT INTERNATIONAL CONFERENCE ON DATA SCIENCE & MANAGEMENT OF DATA, CODS COMAD 2022(2022)
IBM Res
被引用10|浏览49
摘要
This tutorial presents an open source Python package (https://github.com/IBM/UQ360) named Uncertainty Quantification 360 (UQ360), a toolkit that provides a broad range of capabilities for quantifying, evaluating, improving, and communicating uncertainty in the AI application development lifecycle. We will first introduce the concepts in uncertainty quantification through an interactive experience (http://uq360.mybluemix.net) followed by use cases with different quantification algorithms and evaluation metrics. The hands-on experience gained from tutorial will aid researchers and developers in producing and evaluating high-quality uncertainties from AI models in an efficient manner.