Computing Matrix Algebra with R and Rcpp

Explore matrix summation, multiplication, LU factorization, and eigendecomposition. Discover applications in machine learning, signal and image processing.

Intermediate

38 Lessons

19h

Certificate of Completion

Explore matrix summation, multiplication, LU factorization, and eigendecomposition. Discover applications in machine learning, signal and image processing.

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This course includes

61 Playgrounds
12 Quizzes

This course includes

61 Playgrounds
12 Quizzes

Course Overview

Matrix algebra is the foundation for machine learning, signal processing, image processing, and many other popular algorithms. It is very important that aspiring computer scientists get a solid understanding of the subject, and there’s no better way to achieve this than coding matrix algebra operations. The course aims to teach you how to code matrix algebra operations in R, and with main C++ matrix algebra libraries: RcppArmadillo and RcppEigen. Moreover, to clarify the matrix algebra operations, a simpl...Show More

What You'll Learn

An understanding of introductory matrix algebra

Working knowledge of coding matrix algebra operations in R

Ability to implement simple matrix algebra algorithm in Rcpp

Hands on experience of using RcppArmadillo and RcppEigen in R

What You'll Learn

An understanding of introductory matrix algebra

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Course Content

1.

Introduction

Get familiar with practical matrix algebra computation using R, Rcpp, and C++ libraries.
2.

Assignment Operator

Get started with matrix assignments in R and Rcpp, plus a hands-on challenge.
3.

Addition of Matrices

Break apart the principles of matrix addition and reinforce through quizzes and challenges.
4.

Scalar Multiplication of Matrices

Build a foundation in scalar multiplication of matrices with R and Rcpp.
5.

Multiplication of Matrices

Solve problems in matrix multiplication with R and Rcpp through practical exercises and quizzes.
6.

Transposition of Matrices

3 Lessons

Tackle transposing matrices in R and C++, assessing understanding, and checking symmetry.
7.

Determinant of a Matrix

3 Lessons

Practice using tools to calculate, interpret, and analyze matrix determinants efficiently.
8.

Inverse of a Matrix

3 Lessons

Learn how to use R to compute and verify matrix inversions effectively.
9.

System of Linear Equations

3 Lessons

Solve challenges with linear equations using R and C++, including quizzes and coding tasks.

Biostatistics in Medical Study with R

Project

10.

LU Matrix Factorization

3 Lessons

Go hands-on with LU matrix factorization to decompose matrices and efficiently solve linear systems.
11.

Cholesky Factorization

3 Lessons

Break down complex ideas of Cholesky factorization, tests, and practical challenges in R.
12.

QR Matrix Factorization

3 Lessons

Solve problems in QR factorization, validate with quizzes, and implement coding challenges.
13.

Eigendecomposition

3 Lessons

See how it works to decompose matrices into eigenvalues and eigenvectors using R and Rcpp.
14.

Wrapping It Up

1 Lesson

Build on knowledge of matrix algebra and R for future learning opportunities.

Course Author

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