Explore transfer learning in deep learning with a focus on medical imaging applications in this 46-minute lecture by Maithra Raghu from Cornell University and Google Brain. Delve into the fundamentals of transfer learning, its applications in medical imaging, and the evaluation of transfer performance. Examine the relationship between ImageNet model performance and transfer capabilities, analyze chest X-ray results, and learn about Canonical Correlation Analysis (CCA) for feature similarity assessment. Investigate the similarity of deep representations and feature reuse in transfer learning. Conclude by considering open questions in the field, gaining valuable insights into this crucial area of deep learning research.