STAT 227: Stat Learning & Data
University of California, Santa Cruz
Introductions to statistical learning, modeling, and inference with complex, large, and high-dimensional data. Topics include supervised and unsupervised learning, model selection, dimension reduction, matrix factorization, latent variable models, graphical models, interpretability and causality. Applications in health, social sciences, and engineering.
Average GPA: 3.95
Grade distribution records: 12 students across 1 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 2 | 16.7% |
| A | 3 | 25.0% |
| A- | 1 | 8.3% |
| S | 5 | 41.7% |
| U | 1 | 8.3% |
Based on 12 student grade records across 1 term and 1 professor.
Instructors
- Zehang Li 12 students, Average GPA 3.95