Explore the concept of transfer learning in deep neural networks through this 21-minute tutorial. Discover how to adapt pre-trained models for new applications, particularly in microscopy and image classification. Learn about the challenges of limited training data and how transfer learning can help overcome them. Examine a practical example of using feature extraction from a network trained on cat and dog images to classify healthy versus malarial cells. Gain insights into preprocessing techniques and access the accompanying code on GitHub to enhance your understanding of this powerful machine learning technique.