Optimization for Data Science

Subject: 
Combinatorics & Optimization (CO)
Catalog number: 
673
Unit weight: 
0.50
Meet type: 
LEC
Grading basis: 
NUM
Cross-listing(s): 
CS-794
Requisites: 
N/A
Description: 
Techniques for formulating data science models as optimization problems. Algorithms for solving data science problems with an emphasis on scalability, efficiency and parallelizability including gradient-descent based algorithms, derivative-free algorithms, and randomized algorithms. Theoretical analyses of algorithms and approaches for recognizing the most suitable algorithm for solving a particular problem.
Topic titles: 
N/A
Faculty: 
Mathematics (MAT)
Academic level: 
GRD
Course ID: 
015821