CSCC11H3 Introduction to Machine Learning and Data Mining

An introduction to methods for automated learning of relationships on the basis of empirical data. Classification and regression using nearest neighbour methods, decision trees, linear and non-linear models, class-conditional models, neural networks, and Bayesian methods. Clustering algorithms and dimensionality reduction. Model selection. Problems of over-fitting and assessing accuracy. Problems with handling large databases.

Prerequisite: 

MATB24H3 and MATB41H3 and STAB52H3 and [CGPA 3.0 or enrolment in a CSC, STA or Quantitative Analysis Subject POSt].

Exclusion: 

CSC411H, ( CSCD11H3)

Recommended Preparation: 
Breadth Requirements: 
Quantitative Reasoning