Statistical learning
Undergraduate · Math
Syllabus focus
Topics typically covered
Click a topic for the full text and related unit practice.
Undergraduate Statistical learning — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable).
Linear methods for prediction
- Linear regression as a learning method — Linear regression as a learning method
- Subset selection and shrinkage: ridge and lasso — Subset selection and shrinkage: ridge and lasso
- Bias-variance tradeoff — Bias-variance tradeoff
- Cross-validation — Cross-validation
- Model selection — Model selection
- Polynomial and spline regression — Polynomial and spline regression
Classification and beyond
- Logistic regression — Logistic regression
- Linear discriminant analysis — Linear discriminant analysis
- Support vector machines (introduction) — Support vector machines (introduction)
- Decision trees and random forests — Decision trees and random forests
- Neural networks overview (optional) — Neural networks overview (optional)
- Unsupervised learning: clustering and PCA — Unsupervised learning: clustering and PCA
Theory and diagnostics
- Overfitting — Overfitting
- Regularization paths — Regularization paths
- Resampling methods: bootstrap and CV — Resampling methods: bootstrap and CV
- Model interpretation: partial dependence (intro) — Model interpretation: partial dependence (intro)
- Statistical learning vs classical inference — Statistical learning vs classical inference
Study units
Each unit includes a study guide, worksheets, review, practice test, and answer key. One unit is free; subscribe for the full class.
- Linear methods for prediction
Linear regression as a learning method
Coming soon - Classification and beyond
Logistic regression
Coming soon - Theory and diagnostics
Overfitting
Coming soon
Notes
Undergraduate Statistical learning — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable). Topic outline: `content/topics/undergraduate/statistical_learning.json`.