Biostats short course: Introduction to Machine Learning with R
Course taught by Rafael A. Irizarry, PhD, biostatistics professor at the Harvard T.H. Chan School of Public Health and chair of the Department of Biostatistics and Computational Biology at Dana Farber Cancer Institute.
We will assume that you have basic knowledge of R and that you own a laptop with R and RStudio installed. We will use the caret R package. Knowledge of R is a requirement.
What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors. Through examples you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation.
A Wi-fi enabled laptop. We will use the caret R package. Knowledge of R is a requirement.
Rafael A. Irizarry, PhD
Rafael Irizarry is a professor of applied statistics at Harvard T.H. Chan School of Public Health and the Dana-Farber Cancer Institute. He was recently named chair of the Department of Biostatistics and Computational Biology at the Dana-Farber Cancer Institute and is a professor of Biostatistics at Harvard T.H. Chan School of Public Health.