Welcome

I took 6.3900 (6.036) Introduction to Machine Learning at MIT in the Fall of 2022. This is a collection of tools I made for fun to help practice the concepts we learned in class (full notes here). The topics we covered were (in order):

Regression
Gradient Descent
Classifiers and Logistic Regression
Features
Clustering
Neural Networks
Convolutional Neural Networks
State Machines and RNNs
Markov Decision Processes
Reinforcement Learning
Decision Trees and Nearest Neighbor

You can click the items in the list above to check out a tool I made for each topic. They provide visualizations and allow you to do calculations. I hope you find them useful!