What is Transfer learning?

--> Transfer learning is a method of reusing a pre-trained model knowledge for another task. It can be used for classification, regression and clustering problems. It is a long process to collect related training data and rebuild the models. In such cases, Transferring of Knowledge or transfer learning from disparate domains would be desirable.

What is VGG16?

--> VGG is a Convolutional Neural Network architecture, It was proposed by Karen Simonyan and Andrew Zisserman of Oxford Robotics Institute in the year 2014. It was submitted to Large Scale Visual Recognition Challenge 2014 (ILSVRC2014) and The model achieves 92.7% top-5 test accuracy in ImageNet (dataset).

Transfer Learning Using VGG16

--> We can add one more layer or retrain the last layer to extract the main features of our image. We can also give the weight of VGG16 and train again, instead of using random weight (Fine Tuning). Here in this task, we have to do face recognition using transfer learning for the model training. We will use pre-defined weights and will freeze the upper layers or the input layers and will use them as they have weights.

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