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

## Exercise

The following code will generate a randomly distributed grayscale matrix with values from $0$ to $100$. Your challenge is to: 
* Create two `x` and `y` matrices. 
* Multiply them within the `matrix_mul()` function.

Use the code editor below to implement your solution.

> **Note:** You can get help by clicking “Show Solution” under the code

# Exercise

The following code will generate a randomly distributed grayscale matrix with values from $0$ to $100$. Your challenge is to: 
* Create two `x` and `y` matrices. 
* Multiply them within the `matrix_mul()` function.

Use the code editor below to implement your solution.

> **Note:** You can get help by clicking “Show Solution” under the code

Solve this challenge on matrix multiplication 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

Challenge: Matrix Multiplication

Exercise