Introduction to Self-supervised Learning

Intro to Self-supervised Learning

Talk, School of Medicine, University of Washington, Seattle. Sep 5th, 2023

This presentation dive into applications of AI, progressing from modern machine learning techniques to more specific topic self-supervised learning. As the intricate nature of biological data demands sophisticated analytical tools, the gist points of this talk illustrating how self-supervised learning can be adeptly applied to RNA-seq analysis, offering a glimpse into the potential of AI in unraveling complex biological narratives.