In this project we had 2 main objectives: Identifying which pet images are of dogs and which pet images aren't of dogs Classifying the breeds of dogs, for the images that are of dogs Your program should have provided you with objectives 1 and 2 when it was run. In the table below, you will find our results for each of the model architectures. Your program should provide you with the same results as we have provided below.
For objective 1, notice that both VGG and AlexNet correctly identify images of "dogs" and "not-a-dog" 100% of the time. For objective 2, VGG provides the best solution because it classifies the correct breed of dog over 90% of the time.