Statistical Machine Learning is used to discover patterns and relationships in large data sets. Topics will include: data exploration, classification and regression tress, 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, 2

Passtime

None

Level Limit

Letters and science

College
Unlocks PSTAT 135 PSTAT 134 PSTAT 234
These majors only finms actsc stsds stsap stats
T B A
No info found
Lecture
LSB 1001
T R
17:00 PM - 18:15 PM
78 / 80
Sections
PHELP1525
M
10:00 AM - 10:50 AM
18 / 20
PHELP1525
M
11:00 AM - 11:50 AM
20 / 20 Full
PHELP1525
M
12:00 PM - 12:50 PM
20 / 20 Full
PHELP1525
M
13:00 PM - 13:50 PM
20 / 20 Full
See All
Winter 2024 . Coburn K M
ILP 1101
T R
14:00 PM - 15:15 PM
Winter 2024 . Coburn K M
NH 1006
T R
17:00 PM - 18:15 PM
See All
PSTAT 131 Coburn K M Fall 2023 Total: 88
PSTAT 131 Yu G Fall 2023 Total: 62
PSTAT 122
125 / 125 Full
Design and Analysis of Experiments
T B A
T R
08:00 AM - 09:15 AM
PSTAT 126
100 / 100 Full
Regression Analysis
Pandey P
T R
14:00 PM - 15:15 PM
PSTAT 126
100 / 100 Full
Regression Analysis
Pandey P
T R
11:00 AM - 12:15 PM
PSTAT 127
81 / 125 Enrolled
Advanced Statistical Models
Wendy Meiring 3.0
T R
11:00 AM - 12:15 PM
PSTAT 130
102 / 125 Enrolled
SAS Base Programming
Julie Swenson 4.6
T
09:30 AM - 10:45 AM
PSTAT 134
62 / 80 Enrolled
Statistical Data Science
Baracaldo Lan
T R
15:30 PM - 16:45 PM