LINEAR ALGEBRA FOR MACHINE LEARNING
Session
Academic Term
Class Number
32257
Career
Undergraduate
Dates
8/27/2021 - 12/18/2021
Units
3 units
Grading
Letter Grade
Description
Core concepts from linear algebra that are key for understanding and creating applied machine learning algorithms. Topics include least square approximation, neural networks, and matrix factorization for dimension reduction.
Add Consent
Department Consent Required
Class Details
Instructor(s)
N. Benjamin Erichson
Meets
MoWe 4:00PM - 5:15PM
Meeting Dates
08/27/2021 - 12/18/2021
Room
G24 Benedum Hall
Campus
Pittsburgh Campus
Location
Pittsburgh Campus
Components
Lecture Required
Textbooks/Materials
Textbooks to be determined
Class Availability
Status
Open
Seats Taken
16
Seats Open
19
Combined Section Capacity
35
Unrestricted Seats
0
Restricted Seats
0
Wait List Total
0
Wait List Capacity
10
Combined Section
LINR ALG FOR MACHINE LEARNING
MEMS 1300 - 1080 (32257)
Status: Open
Seats Taken: 2
Wait List Total: 0
LINR ALG FOR MACHINE LEARNING
ME 2300 - 1080 (32258)
Status: Open
Seats Taken: 14
Wait List Total: 0
LINR ALG FOR MACHINE LEARNING
ENGR 2300 - 1080 (32259)
Status: Open
Seats Taken: 0
Wait List Total: 0