Hands-on Machine Learning

In this unit we introduce the field of Machine Learning (ML) and develop the first set of techniques for supervised learning. We will explore key ML concepts, including supervised classification, linear regression, nearest neighbor, logistic regression, and decision trees, with a focus on ML considerations and evaluation in life science applications.

• Introduction to Machine Learning
• Linear Regression
• Classification: A First Look
• Measuring and Validating Classification Model Quality
• Nearest Neighbor Classification
• Decision Tree and Random Forest
• Logistic Regression and Naive Bayes
• Data Standardization And Pipelines