Universidad Panamericana
Course Description
The second course in the machine learning track. Builds on foundational ML to cover advanced supervised and unsupervised methods, model selection, and applied modeling workflows.
Syllabus
| Week | Topic |
|---|---|
| 1 | Review: bias/variance, cross-validation |
| 2 | Regularized linear models |
| 3 | Tree-based methods and ensembles |
| 4 | Gradient boosting (XGBoost, LightGBM) |
| 5 | Support Vector Machines and kernels |
| 6 | Unsupervised learning: clustering and dimensionality reduction |
| 7 | Model interpretability and feature importance |
| 8 | Applied modeling project |
(Replace this table with the actual schedule once finalized.)
Materials
- Slides:
- Notebooks:
- Readings:
Assessment
- Homework:
- Project:
- Final exam:
Schedule & Office Hours
- Lectures:
- Office hours:
- Contact: