Principal Component Analysis (PCA) is an unsupervised learning algorithms and it is mainly used for dimensionality reduction, lossy data compression and feature extraction. It is the mostly used unsupervised learning algorithm in the field of Machine Learning. In this video tutorial, after reviewing the theoretical foundations of Principal Component Analysis (PCA), this method is implemented step-by-step in Python and MATLAB. ...

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, ...