COMP 542: MACHINE LEARNING
California State University, Northridge
Prerequisites: COMP 380/L or equivalent; MATH 262 or equivalent; MATH 340 or MATH 341 or equivalent. Recommended Preparatory: Knowledge of Python programming. A study of the concepts, theories, techniques, and applications of machine learning. Students will get exposure to a broad range of machine learning methods and hands on practice on real data. Topics may include feature selection, feature transformation, dimensionality reduction, concept-based learning, distance-based learning, Bayesian classification and networks, regression analysis, kernel methods, support vector machines, decision trees, explainable AI, basic neural networks, and machine learning on the cloud.
Average GPA: 3.49
Grade distribution records: 559 students across 12 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A | 254 | 45.4% |
| A- | 88 | 15.7% |
| B+ | 64 | 11.4% |
| B | 87 | 15.6% |
| B- | 21 | 3.8% |
| C+ | 15 | 2.7% |
| C | 15 | 2.7% |
| C- | 4 | 0.7% |
| D+ | 2 | 0.4% |
| D | 4 | 0.7% |
| D- | 1 | 0.2% |
| F | 4 | 0.7% |
Based on 559 student grade records across 12 terms and 5 professors.
Instructors
- Taehyung Wang 169 students, Average GPA 3.40
- Rashida Hasan 163 students, Average GPA 3.70
- Mansoureh Lord 83 students, Average GPA 3.22
- Wonjun Lee 51 students, Average GPA 3.16
- Sevada Isayan 24 students, Average GPA 4.00