Deep Learning CNN Convolutional Neural Networks with Python - Why Transfer Learning

The video explains transfer learning, where a pre-trained model is adapted for custom data. It describes how early layers detect basic features, while deeper layers identify complex patterns. The process involves freezing initial layers and appending custom architecture. Transfer learning is effective in various applications, as demonstrated by models like AlexNet.

Why do we freeze the initial layers of a deep learning model when using transfer learning?

What makes transfer learning successful according to the text?