This repository is a collection of my work done at Northwestern University's machine learning course COMP349. Inside each reporsitory, code for both the algorithms and comprehension questions are included. All test cases are passed and can be checked by $python -m pytest

Topics Covered

1. Decision tree
2. Multiple Regression & Perceptron
3. K-Nearest-Neighbor
4. Support Vector Machine
5. Reinforcement Learning
6. K-means & Gaussian Mixture
7. Gradient Descent
8. Deep Neural Networks

• Python 3.6
• Anaconda