Introduction to Machine Learning
|Hours||3.0 Credit, 3.0 Lecture, 0.0 Lab|
|Prerequisites||C S 312 & MATH 215 & STAT 121; or C S 312 & MATH 215 & STAT 201; or C S 312 & MATH 313 & STAT 121|
|Note||Students are allowed 1 repeat of each C S undergraduate course (all 100-, 200-, 300- or 400-level courses). This includes all students who received any grade including those who withdraw (receive a "W" grade) from a C S course. Students must wait 1 semester/term before being allowed to take a course they have failed twice. Petitions for exceptions to the policy can be completed at cs.byu.edu/undergraduate-handbook/retake-policy-cs-courses/.|
|Programs||Containing C S 472|
Use Effective Machine Learning Techniques
You will learn the basic theory and models used in machine learning
You will be able to recognize when machine learning and data mining tools are applicable.
You will be able to plan and execute successful machine learning and data mining projects, including selecting an adequate process for your specific task and avoiding the main machine learning pitfalls.