STAT433Undergraduate
Statistical Machine Learning
Printed in the catalogue as STATISTICAL MACHINE LEARNING
Course content
Regression and prediction, optimization, regularization (Ridge regression and LASSO), neural networks and deep learning, classification, kernel methods and support vector machines, decision trees, bagging and random forest, boosting algorithms, principal component regression, unsupervised deep learning. Applying the methods to real data.
Where it sits in a curriculum
Programs whose published curriculum lists this course, and the term it falls in. Your own curriculum is the one that counts.
- StatisticsYear 4, Spring semester
More in STAT
- STAT101Introduction to Statistics and Data Science I
- STAT102Introduction to Statistics and Data Science II
- STAT112Introduction to Data Processing and Visualization
- STAT201Introduction to Probability &stat. I
- STAT202Introduction to Probability &stat.ii
- STAT203Probability I
- STAT204Probability II
- STAT221Fundamentals of Statistics