Covariance and the correlation matrix - with simple examples

PCA : the basics - explained super simple

Covariance, Clearly Explained!!!

PCA : standardization and how to extract components

Canonical Correlation Analysis (CCA)

How to choose an appropriate statistical test

The Covariance Matrix : Data Science Basics

Validation techniques - explained with simple examples (Hold-out, cross-validation, LOOCV)

How to derive a correlation matrix from a covariance matrix #statistics #matrix

PCA : the math - step-by-step with a simple example

Linear discriminant analysis (LDA) - simply explained

Algebra Basics: What Is Algebra? - Math Antics

PCA : how to interpret the weights/loadings and Varimax rotation

Logistic regression : the basics - simply explained

Linear discriminant analysis (LDA) - how to use it as a classifier

Euclidean distance and the Mahalanobis distance (and the error ellipse)

Canonical correlation analysis - explained

ROC and AUC, Clearly Explained!

Decision and Classification Trees, Clearly Explained!!!

Hotelling's T-square - explained with a simple example

Taylor series | Chapter 11, Essence of calculus