This work is related to the Intro to Machine Learning with Pytorch Nanodegree Program that I'm working on in September 2020. The image classfier project asks us to use PyTorch to predict the species based on flower images.

Image Classifier Project.ipynb uses a pretrained network and trains the classifier using the training data. Evaluates accuracy on test, and then on validation. Saves the resulting model. Finally, applies the train network to make prediction for individual jpg images. Program is set to work on either the GPU or CPU.

This part turns the results from Part I into a command line train.py is the command line application used to train the model. predict.py is the command line application to predict the most likely species based on a jpg image of a flower.