Repository for various machine learning implementations for me research.

Given a very specific setup of training data:

1. .pkl files are all located in a separate directory: prep-pkl
2. Update the location of the desired .pkl file in learnme.py (or relevant notebook)
3. Run: ./learnme.py with the following optional arguments (they indicate True if present, False if not): 1. --track_preds (-tp), 2. --err_n_scores (-es), 3. --learn_curves (-lc), 4. --valid_curves (-vc), and 5. --test_compare (-tc)
4. cleanup and store results; update results paths in plotme.py
5. Graph results via: ./plotme.py