The Art of Machine Learning

4.0 credits

Machine Learning (ML) is the branch of Artificial Intelligence dedicated to teaching computers how to solve tasks by learning from data. This class introduces basic concepts of machine learning through various real-world ECE applications. It will cover various learning paradigms such as supervised learning, semi-supervised learning, unsupervised learning, and reinforcement learning. It will also cover classical and state-of-the-art techniques such as linear models, support vector machines, Gaussian mixture models, hidden Markov models, matrix factorization, ensemble learning, principal component analysis, and various kinds of deep neural networks. Students will learn the pros and cons of different methods and their suited application scenarios. This course is hands-on with multiple programming assignments and a final project to solve real ECE problems.