Various convergence acceleration techniques developed in computational mathematics can and have been applied to speed up the convergence of EM and MM algorithms. This monograph will present and discuss these convergence acceleration schemes, with applications and demonstrations using R and Julia code. The monograph will likely be useful to PhD-level graduate students and researchers in statistics, data science, applied mathematics, engineering, and physics working on computational algorithms for big data and high-dimensional problems.