Learn how to code matrix algebra operations in R with the main C++ matrix algebra libraries: RcppArmadillo and RcppEigen.

Become an R Developer

This module aims to teach us how to code matrix algebra operations in R and with the main C++ matrix algebra libraries: RcppArmadillo and RcppEigen. Moreover, to clarify the matrix algebra operations, we’ll go through a simple algorithm to understand the computing implications. By the end of this module, we’ll have hands-on experience in performing matrix algebra computation in the R and Rcpp ecosystem, and the ability to develop algorithms for areas such as machine learning, image processing, and signal processing.

Computing Matrix Algebra with R and Rcpp

Becoming a competent data scientist requires a lot of dedication, hard work, and comfort with matrices.

The **matrix** is a tidy mathematical object with its own set of rules. Its algebra helps us understand matrix structure and its interactions with other matrices, vectors, and scalars.

This module will improve our ability to interact with matrices by teaching us to compute important matrix algebra operations.
# About this module

Data is represented in computers as **math objects**, such as matrices and vectors. Data scientists interact with data through these computational tools.

This module is an agile review of algebra operations on matrices through coding in R, Rcpp, Armadillo, and Eigen to better understand the matrix object.

Learn about matrices and how to perform different algebraic operations in R.

Introduction

Assignment Operator

Addition of Matrices

Scalar Multiplication of Matrices

Multiplication of Matrices

Transposition of Matrices

Determinant of a Matrix

Inverse of a Matrix

System of Linear Equations

Conclusion

Get Started with Matrix Algebra

About this module