CS181 Machine Learning, Teaching Fellow, Spring 2022

Undergraduate course, Harvard University, 2022

CS181 provides a broad and rigorous introduction to machine learning, probabilistic reasoning and decision making in uncertain environments. Topics include: supervised learning, ensemble methods and boosting, neural networks, support vector machines, kernel methods, clustering and unsupervised learning, maximum likelihood, graphical models, hidden Markov models, inference methods, reinforcement learning.

Link to CS181 website.