Projects folder for my course on AI Programming with Python Nanodegree with Udacity
In this project we used a created image classifier to identify dog breeds. The focus was on python coding rather than the classifier.
1. Correctly identify which pet images are of dogs (even if breed is misclassified) and which pet images aren't of dogs.
2. Correctly classify the breed of dog, for the images that are of dogs.
3. Determine which CNN model architecture (ResNet, AlexNet, or VGG), "best" achieve the objectives 1 and 2.
4. Consider the time resources required to best achieve objectives 1 and 2, and determine if an alternative solution would have
given a "good enough" result, given the amount of time each of the algorithms take to run.
The project was in 2 parts: a. In this first part, we worked through a Jupyter notebook to implement an image classifier with PyTorch. b. In the second part, we built a command line application from the first part that others can run from a terminal.