Supervised Learning I

Course ID DSCI 571

Campus UBC Vancouver

Semester Fall

Course Block 2

Course Description Fundamental concepts and techniques of supervised machine learning, including data splitting, cross-validation, generalization, overfitting, the bias–variance trade-off, the golden rule, and data preprocessing. You will also learn popular machine learning algorithms such as decision trees, k-nearest neighbours, SVMs, naive Bayes, and linear models using the scikit-learn framework.

Instructor(s) with link Varada Kolhatkar (Section 1 and 2)