Moving from Offline to Online Machine Learning with River - Data Science Festival

A talk by Tun Shwe from Quix. The foundations of machine learning were built on offline batch processing techniques for model training and inference. As organisations become more dependent on real-time data, the technological trend for machine learning in production is moving towards adding an online stream processing approach. This has benefits such as lower computational requirements due to being able to incrementally learn from a stream of data points, which enables the continual upgrading of models by adapting to real-time changes in data. Technical Level: Introductory level/students This session was part of the Data Science Festival Oktoberfest event 2024. Find out more at https://datasciencefestival.com/event/oktoberfest-2024/ The Data Science Festival is the place for data-driven people to come together, share cutting-edge ideas, and solve real-world problems. We run monthly events, meet-ups, and the biggest free-to-attend data festivals in the UK. Join the community at https://datasciencefestival.com/