Data Science
Supervised Learning II
1 credits
Support Vector Machines. Random Forests. Ensemble Classifiers. Graphical models.
Average
88.6%
Students
907
Sections
16
Grade distribution. <50: 0, 50-54: 0, 55-59: 0, 60-63: 0, 64-67: 7, 68-71: 3, 72-75: 13, 76-79: 56, 80-84: 126, 85-89: 205, 90-100: 487.
Historical Averages
2016–2024
Lowest section avg
85.4%
Highest section avg
93.4%
Terms offered
9
Some grade ranges were withheld by UBC to protect student privacy and are not shown above.
Grade data from ubc-pair-grade-data.
| Section | Activity | Status | Time | Instructor |
|---|---|---|---|---|
| 001 | Lecture | Open | Mon 11:00-12:30, Wed 11:00-12:30 | Varada Kolhatkar |
| 002 | Lecture | Open | Tue 09:30-11:00, Thu 09:30-11:00 | Prajeet Bajpai |
| 003 | Lecture | Open | Tue 11:00-12:30, Thu 11:00-12:30 | Jian Zhu |
| L01 | Laboratory | Open | Wed 14:00-16:00 | Varada Kolhatkar |
| L02 | Laboratory | Open | Mon 14:00-16:00 | Varada Kolhatkar |
| L03 | Laboratory | Open | Thu 14:00-16:00 | Prajeet Bajpai |
| L04 | Laboratory | Open | Tue 14:00-16:00 | Prajeet Bajpai |
| L05 | Laboratory | Open | Thu 14:00-16:00 | Jian Zhu |
| L06 | Laboratory | Open | Thu 16:00-18:00 | Jian Zhu |
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