ECE 172 - Fundamentals of Machine Learning

Prerequisite: ECE 72 and ECE 125
Linear regression, SSR, gradient descent, overfitting and complexity; training; validation, test data classification problems, decision boundaries, nearest neighbor methods, probability and classification. Bayes optimal decisions, linear classifiers, neural networks, decision tree, ensemble methods, clustering, supervised and unsupervised learning, PCA, SVM.

Units: 3