Transfer-Learning-with-MobileNetV2-for-Cats-vs-Dogs-Image-Classification

This project is an image classification project based on a transfer learning approach using with MobileNetV2 architecture.

This project is an improvement on a previous project in which we built and trained a custom deep CNN from the ground up.

Finally, this project demonstrates the power of transfer learning; in fact, we achieved a model accuracy of 98.51% using only 50% of the train dataset, whereas the previous project only achieved 94% accuracy using all available data.

You can find a link provided by microsoft to the dataset used in ths project here .

You can find the model weights and history logs here

testing predictions

Confusion matrix