-
Course
- Data
Applying Linear Algebra with R
Take this course if you want to dive into the math behind regression, principal component analysis, and other machine learning topics. The course is in R and is mathematically intense, but the topics can be implemented in any programming language.
What you'll learn
Would you like to better understand the basics of linear algebra so that you can better understand the techniques used in regression and machine learning? In this course, Applying Linear Algebra with R, you will learn foundational knowledge to understand what is going on in predictive models, how to extract important information from large data sets, and the basics of linear regression in R. First, you will learn basic matrix arithmetic. Next, you will discover advanced matrix mathematics that will help build your foundation. Finally, you will explore how to put this math together into real world applications. When you are finished with this course, you will have the skills and knowledge of Linear Algebra in R needed to better implement basic machine learning techniques and springboard into more advanced topics like generalized linear models.
Table of contents
About the author
Brandon has a BSc in Mathematics and is a master’s candidate for Predictive Analytics at Northwestern University. He learned R from scratch and is here to make sure you don’t have to.
More Courses by Brandon