Introduction to Machine Learning
Introduction to Machine Learning
Machine learning models and other mechanisms allowing computers to learn and find knowledge from data.
| 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 only 1 retake of CS 472. This includes students who have failed or withdrawn (received a "W" grade). If after 1 retake, a student needs to retake the course again, the student must wait 1 semester/term before being allowed to take any C S course and must follow the petition process at cs.byu.edu/retake-policy. This policy does not apply to classes dropped before the add/drop deadline. Petitions for exceptions to the policy can be completed at cs.byu.edu/retake-policy. |
| Taught | Fall, Winter |
| Programs | Containing C S 472 |
Course Outcomes:
Use Effective Machine Learning Techniques
You will learn the basic theory and models used in machine learning
Recognize
You will be able to recognize when machine learning and data mining tools are applicable.
Execute
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.