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CS 345 - Machine Learning Foundations and Practice

  • 3 credits
View available sections

Machine learning algorithms and tools for predictive modeling presented using case studies that inform their use in real-world applications. Credit not allowed for both CS 345 and DSCI 445 (Statistical Machine Learning).

Prerequisite

CS 220 (Discrete Structures and their Applications); CS 150B (Culture and Coding: Python (GT-AH3)) or CS 152 (Introduction to Programming (CS0)-Python) or CS 165 (CS2 Data Structures) or DSCI 235 (Data Wrangling); MATH 155 (Calculus for Biological Scientists I) or MATH 156 (Mathematics for Computational Science I (GT-MA1)) or MATH 159 (One Year Calculus IB (GT-MA1)) or MATH 160 (Calculus for Physical Scientists I (GT-MA1)); Textbooks and Materials

Please check the CSU Bookstore for textbook information. Textbook listings are available at the CSU Bookstore about 3 weeks prior to the start of the term.

Instructors

Nikhil Krishnaswamy

Nikhil.Krishnaswamy@colostate.edu