• Trained a neural network on a dataset of dogs to achieve 84% test accuracy in classifying 7 breeds of dogs.

• Improved test accuracy to 99.8% using neural networks such as ResNet18, ResNet34, and ResNeXt32 by freezing all but the last few layers of the networks.

• Making use of another dataset, created a neural network to distinguish between dog images of the two datasets, achieving a test accuracy of 94.4%