Computing Matrix Algebra with R and Rcpp

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 simple algorithm is provided to understand the computing implications. The provided matrix algebra operations range from matrix summation and matrix multiplication to LU factorization and eigendecomposition. The main course outcome is to develop hands-on experience via curated programs to perform the matrix algebra computation in the R and Rcpp ecosystem, also including the ability to develop algorithms for areas such as machine learning, image processing and signal processing.