MATH 156 - Machine Learning
Lecture: Lec 1
Class ID: 262580110
Class Website: https://ccle.ucla.edu/course/view/201A-MATH156-1
Final Exam Information
Consult instructor for method of evaluation
Lecture, three hours; discussion, one hour. Requisites: courses 115A, 164, 170A or 170E or Statistics 100A, and Computer Science 31 or Program in Computing 10A. Strongly recommended requisite: Program in Computing 16A or Statistics 21. Introductory course on mathematical models for pattern recognition and machine learning. Topics include parametric and nonparametric probability distributions, curse of dimensionality, correlation analysis and dimensionality reduction, and concepts of decision theory. Advanced machine learning and pattern recognition problems, including data classification and clustering, regression, kernel methods, artificial neural networks, hidden Markov models, and Markov random fields. Projects in MATLAB to be part of final project presented in class. P/NP or letter grading.
General Education (GE)
This class does not satisfy any GE requirements.
This class does not satisfy the undergraduate Writing II requirement.
This class does not satisfy any College/School diversity requirement.
- College of Letters and Science
Materials Use Fee