What is Principal Component Analysis? Principal Component Analysis (PCA) is a statistical procedure and an Unsupervised Learning Algorithm for reducing the dimensionality of a data set while retaining as much information as possible. PCA does this by finding a set of new variables, called “Principal Components”, that are linear combinations of the original variables. The principal components are chosen so ...

In this video tutorial, the theory of Runge-Kutta Method (RK4) for numerical solution of ordinary differential equations (ODEs), is discussed and then implemented using MATLAB and Python from scratch. As an example, the well-know Lotka-Volterra model (aka. the Predator-Prey model) is numerically simulated and solved using Runge-Kutta 4th order (RK4), in both languages, Python and MATLAB. After completing this tutorial, ...