Human Being can process images easily. It’s very easy for us to distinguish between various objects that we come across in our daily life. These tasks which are quite rudimentary for the human brain tend to be very hard problems when the computers are involved in solving the problem. The image recognition is easy to us because we have been trained to recognize the objects through their images since infancy. Machine Learning fields over the last few years have made exceptional progress in this field. But training the computer for the same thing requires a lot of time and effort. This is where Transfer Learning comes into play. We will be using transfer learning on the basic TensorFlow library to train our module on Oxford 17 VGG and Oxford 102 VGG flower data sets. We have majorly used Google’s Inception v3 model and applied it on Oxford data set to categorize flowers. This gave an overall accuracy of 94.8%.