ELEG 605 - Engineering Machine Learning Systems

Credit(s): 3

ENGINEERING MACHINE LEARNING
Component: Lecture
Engineering Machine Learning Systems are applied in an array of real-world applications. This course focuses on their conceptualization, estimation, computational implementation, and optimization. Topics supervised and unsupervised learning, linear and logistic regression, dimensionality reduction, regularization, neural networks, convolution neural networks, decision trees, and select additional deep learning topics.
Repeatable for Credit: N Allowed Units: 3 Multiple Term Enrollment: N Grading Basis: Student Option
PREREQ: Basic probability theory, discrete math, simple calculus, linear algebra (preferred), and programming experience, particularly in Python, or equivalents.

Course Typically Offered: Fall