This is Part II of a 2 part series that cover fine-tuning deep learning models in Keras. Part I states the motivation and rationale behind fine-tuning and gives a brief introduction on the common practices and techniques. This post will give a detailed step-by-step guide on how to go about implementing fine-tuning on popular models VGG, Inception, and ResNet in Keras.

In this post, I am going to give a comprehensive overview on the practice of fine-tuning, which is a common practice in Deep Learning.