Moving from Offline to Online Machine Learning with River

Learn about transitioning from offline to online machine learning in this 50-minute introductory talk presented by Tun Shwe from Quix at the Data Science Festival Oktoberfest 2024. Explore how organizations are shifting from traditional offline batch processing to online stream processing approaches for machine learning in production environments. Discover the advantages of incremental learning from data streams, including reduced computational requirements and the ability to continuously update models based on real-time data changes. Gain foundational knowledge suitable for students and newcomers to machine learning while understanding the evolving landscape of real-time data processing in modern organizations.