Christopher Risi
Christopher is a computer science Ph.D. student from the University of Waterloo, specializing in artificial intelligence. Christopher is a member of the Computational Health Informatics Lab (CHIL), a Consultant, AI Research & Health Insights at Gluroo Imaginations Inc., and co-founder of the Blood Glucose Control AI Design Team.
Christopher's research focuses on developing AI systems for aiding and supporting decision making in the management of diabetes.
LinkedIn: https://www.linkedin.com/in/christopherrisi/
BGC AI Design Team: https://github.com/RobotPsychologist/bg_control/wiki/About-Us
Sessions
skchange is a python compatible framework library for detecting anomalies, changepoints in time series, and segmentation.
skchange is based on and extends sktime, the most widely used scikit-learn compatible framework library for learning with time series. Both packages are maintained under permissive license, easily extensible by anyone, and interoperable with the python data science stack.
This workshop gives a hands-on introduction to the new joint detection interface developed in skchange and sktime, for detecting point anomalies, changepoints, and segment anomalies, in unsupervised, semi-supervised, and supervised settings.