Introduction to Machine Learning (ECE 146)
This is a senior level undergraduate class that introduces the principles of Machine Learning and encompasses the study of algorithms that learn from data. This class will introduce the fundamental concepts and algorithms in machine learning (supervised as well as unsupervised learning) as well as best practices in applying machine learning to practical problems. The topics covered include basic algorithms of learning such as Decision Trees, Nearest Neighbor Classification, Logistic and Linear regression, Kernel methods, Support Vector Machines, Boosting, PCA and dimensionality reduction, Clustering, Hidden Markov Models and a brief introduction to Neural Networks. The class consists of lectures, problem sets that contain mathematical and programming exercises and in-class exams.
This course was taught at UCLA in Spring 2017-18.