Add homework 4 files
Add prototype notebook for computing features and fitting RF model
Make sure to scale images to all have the same size
Move some of the image processing/feature extraction code into image_processing.py
Use smaller images and fewer HOG features
Move machine learning code into image_classification.py
Move code into new load_and_extract function
Reproducible randomness; run classification on verification set
Some code cleanup; adding docstrings
Add helpful error message if the wrong number of arguments are passed
Add helpful command-line bash script for classifier verification
Add utility library
Compute accuracy for random guessing
Add cross-validation function
Code cleanup; add more docstrings
Add module docstrings
Print out the most important features
Add README.md
Don't use HOG features, there are too many
Allow final classification to take also the path to the classifier