COURSE DESCRIPTION

Regression is a large subset of Machine Learning problems that involves predicting a numerical value using known variables without having to personally work out relationships between those. While this course’s main focus is on constructing and utilizing an appropriate Regression model on a determined problem, you must also understand specific concepts that are universal to Machine Learning as a whole.

LEARNING OUTCOMES

• Understand regression problems in machine learning
• Understand and practice Simple Linear Regression and Multiple Regression
• Understand metrics, why and how are they used for Assessing Performance
• Understand what is Overfit, why it happens and how it impact model quality
• Understand and practice Ridge Regression and LASSO Regression to resolve Overfit
• Understand and practice K-Nearest Neighbor and Kernel Regression
• Apply all learned techniques to solve real-world problems