STATS 231C
Theories of Machine Learning
Statistics · 4 units · Graduate courses (200-299)
Introduction to many useful nonparametric techniques such as nonparametric density estimation, nonparametric regression, and high-dimensional statistical modeling. Some semiparametric techniques and functional data analysis.
Letter grading.
Requisites
Official UCLA wording
Requisites: courses 200A, 231B.
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
STATS 231C
- STATS 200AApplied Probability
- STATS 100AIntroduction to Probability
- MATH 170AProbability Theory I
- STATS 231BMethods of Machine Learning
- STATS 208Statistical Learning Theory
- STATS M231APattern Recognition and Machine Learning
2 direct requisites. Showing 11 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.
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What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.