ME 107: MACHINE LEARNING
University of California, Santa Barbara
This course is meant to introduce students to machine learning and deep lea rning. ME 107 is taught at the undergraduate level and teaches students how to identify a machine learning problem in the context of real-world applic ations, mathematically formulate a learning problem, identify when a learni ng problem is well-posed, under-determined and overdetermined, and develop algorithms and Python code to solve the problem. Students are introduced to the concepts of learning algorithms, overfitting, under-fitting, statistic al measures of estimators, optimization approaches to learning, principal c omponent analysis, regression, support vector machines, and artificial neur al networks.
Average GPA: 3.61
Grade distribution records: 314 students across 4 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 42 | 13.4% |
| A | 133 | 42.4% |
| A- | 63 | 20.1% |
| B+ | 19 | 6.1% |
| B | 26 | 8.3% |
| B- | 11 | 3.5% |
| C+ | 6 | 1.9% |
| C | 5 | 1.6% |
| D+ | 2 | 0.6% |
| D | 3 | 1.0% |
| D- | 1 | 0.3% |
| F | 3 | 1.0% |
Based on 314 student grade records across 4 terms and 1 professor.
Instructors
- Yeung E H 314 students, Average GPA 3.61