These are a few assignments from my machine learning class that I enjoyed working on. I've omitted assignments regarding perceptrons and neural networks, since I already have a neural network program up on github that closely matches what I used for my assignments.
All assignments were written in Python using NumPy for computation and PyPlot for visualizations.
- SVM.py: SVM script using scikit-learn's SVM package, performed cross-validation for finding the best parameters and feature selection
- KNN.py: K-Nearest Neighbors script applied to a digits dataset. This was especially interesting, since the centroids could be redrawn to see what the mean of that centroid looks like
- Bayesian.py: Bayesian learning script that performed quite poorly, was interesting to write