Deep Learning with Python (Video 11)

The video tutorial discusses the use of pre-trained models in deep learning, emphasizing the benefits of using models like AlexNet and GoogleNet instead of training from scratch. It introduces the Cats vs Dogs classification problem and explains how to leverage pre-trained models for feature extraction and transfer learning. The tutorial also highlights various applications of pre-trained models, showcasing their versatility and effectiveness in different tasks.

What new insight or understanding did you gain from this video?