In Part 5 Series of the Transfer Learning series we have discussed the Residual Nets in depth along with hands-on application of these pre-trained neural nets in Keras and PyTorch API’s. The datasets on which these pre-trained model is trained for the ILVRC competition which is held annually and their…

In Part 5.0 of the Transfer Learning series we have discussed about ResNet pre-trained model in depth so in this series we will implement the above mentioned pre-trained model in PyTorch. This part is going to be little long because we are going to implement ResNet in PyTorch with Python…

In Part 5.0 of the Transfer Learning series we have discussed about ResNet pre-trained model in depth so in this series we will implement the above mentioned pre-trained model in Keras. We will be implementing the pre-trained ResNet model in 4 ways which we will discuss further in this article…

In Part 4 Series of the Transfer Learning series we have discussed the VGG nets in depth along with hands-on application of these pre-trained neural nets in Keras and PyTorch API’s. The datasets on which these pre-trained model is trained for the ILVRC competition which is held annually and their…

In Part 4.0 of the Transfer Learning series we have discussed about VGG-16 and VGG-19 pre-trained model in depth so in this series we will implement the above mentioned pre-trained model in PyTorch. This part is going to be little long because we are going to implement VGG-16 and VGG-19…

In Part 4.0 of the Transfer Learning series we have discussed about VGG-16 and VGG-19 pre-trained model in depth so in this series we will implement the above mentioned pre-trained model in Keras. This part is going to be little long because we are going to implement VGG-16 and VGG-19…

In Part 3 of the Transfer Learning series we have discussed the datasets on which these pre-trained model is trained for the ILVRC competition which is held annually and their repository as well as the documentation in order to implement this concept with two API’s namely Keras and PyTorch. In…

In Part 2 of the Transfer Learning series we have discussed, we have discussed how we can set-up our environment in Jupyter Notebook which is compatible with Colab, Binder and in our Local System also. We also discussed what if Transfer Learning how we can use it with less data…

In the previous article, we discussed the layout of the Transfer Learning Series. In this article we will have a deep intuition about Transfer Learning and installation of libraries in which we will implement these concepts. 1. Library Installation We will use two API’s which are mentioned below: Keras: It is most widely…