Build a cat breed image classification model with the architecture specified below.
Dataset - https://www.kaggle.com/ma7555/cat-breeds-dataset
● The classifier should only be trained on these 10 breeds : Bombay, Calico, Burmese, Himalayan, Munchkin, ragdoll, siberian, British shorthair, Russian Blue, Dilute Calico.
● Any of these frameworks can be used : Tensorflow, Keras, Pytorch, Caffee.
● The classifier should only be built using Inception CNN architecture.
● Evaluation metrics i.e Accuracy, Confusion Matrix, F1 Score, ROC-AUC Score shall be calculated on test data.
● The entire process should be clearly logged in a Jupyter Notebook and uploaded to a public github repo, the exact link to this notebook is to be submitted as a result of this assignment.