COGS 118A

Instructor: Zhuowen Tu

Quarters: Fall 2023

This course introduces students to fundamental algorithms used in supervised machine learning such as linear regression, logistic regression, support vector machines, decision trees, random forests, perceptrons, and neural networks. Students learn how to implement these techniques in Python and use them to solve real-world problems. The course contains programming assignments where students use Python packages such as NumPy, Pandas, and Scikit-learn to implement these algorithms. The course ends in a final project where students experiment with different algorithms on different datasets and present their findings.