BIOL420/701: Machine learning in biology

This advanced course introduces students to the principles and practice of machine learning, tailored for applications in biology.

The course covers topics such as: - Bias-variance tradeoffs, validation, testing, and overfitting - Classification and regression trees - Ensemble learning - Support vector machines - Neural networks and deep learning - Best practices

Students work in R or Python (or both), learning through worked examples and small-to medium-scale exercises. The course culminates in a final project applying machine learning to a biological problem of the student’s choice.