Deep Learning for Biomedical Data
2 credits - Spring Term
Deep learning is a branch of machine learning that leverages multiple layers of data representations to capture complex data patterns at various levels of abstraction. Inspired by the organization of neurons in biological systems, deep learning has demonstrated exceptional performance in many tasks, including image classification, natural language processing, and protein structure prediction. This course will introduce the fundamental principles of deep neural networks and GPU computing, discuss convolutional neural networks and transformer architectures, and examine key biomedical applications. Students are expected to be familiar with linear algebra and machine learning and will participate in a group project.
Associate Professor of Biomedical Informatics, Harvard Medical School
Assistant Professor of Pathology, Brigham and Women's Hospital
Instructor in Epidemiology, Harvard T.H. Chan School of Public Health