Transfer Learning in Keras (Image Recognition)

Transfer Learning in AI is a method where a model is developed for a specific task, which is used as the initial steps for another model for other tasks. Deep Convolutional Neural Networks in deep learning take an hour or day to train the mode if the dataset we are playing is vast. The approach is we reuse the weights of the pre-trained model, which was trained for some standard Computer Vision datasets such as Image classification (Image Net). Extensive deep Convolutional networks for large-scale image classification are available in Keras, which we can directly import and can be used with their pre-trained weights. Let's now understand how to use VGG16 pre-trained on 10,000 categories(Image Net) for the Distracted driver Detection dataset.