Statistical Machine Learning is used to discover patterns and relationships in large data sets. Topics will include: data exploration, classification and regression trees, random forests, clustering and association rules. Building predictive models focusing on model selection, model comparison and performance evaluation. Emphasis will be on concepts, methods and data analysis; and students are expected to complete a significant class project, individual or team based, using real world data.

Prerequisites: PSTAT 120A-B; and PSTAT 126 with a minimum grade of C or better.

4

Units

Optional

Grading

1

Passtime

None

Level Limit

Letters and science

College
Unlocks PSTAT 135 PSTAT 134 PSTAT 234
These majors only stats
T B A
No info found
Lecture
LSB 1001
T R
17:00 PM - 18:15 PM
12 / 20
Sections
PHELP1525
M
10:00 AM - 10:50 AM
5 / 5 Full
PHELP1525
M
11:00 AM - 11:50 AM
2 / 5
PHELP1525
M
12:00 PM - 12:50 PM
0 / 5
PHELP1525
M
13:00 PM - 13:50 PM
5 / 5 Full
Spring 2024 . Coburn K M
NH 1006
T R
15:30 PM - 16:45 PM
See All
PSTAT 231 Coburn K M Fall 2023 Total: 25
PSTAT 231 Coburn K M Spring 2023 Total: 18
PSTAT 131
78 / 80 Enrolled
Introduction to Statistical Machine Learning
T B A
T R
17:00 PM - 18:15 PM
PSTAT 134
62 / 80 Enrolled
Statistical Data Science
Baracaldo Lan
T R
15:30 PM - 16:45 PM
PSTAT 223A
20 / 20 Full
STOCHASTIC CALCULUS AND APPLICATIONS
Fouque J-P
M W
11:00 AM - 12:15 PM
PSTAT 227
20 / 30 Enrolled
Bootstrap and Resampling Methodology
Andrew Carter 3.3
T R
09:30 AM - 10:45 AM
PSTAT 234
12 / 20 Enrolled
Statistical Data Science
Baracaldo Lan
T R
15:30 PM - 16:45 PM
CMPSC 9
83 / 150 Enrolled
Intermediate Python Programming
Richert Wang 5.0
T R
15:30 PM - 16:45 PM