Gradient Descent is an algorithm that tries to seek the best values of predictors that give the lowest error.
Dimensionality Reduction Through Principal Component Analysis
Using anova() to compare 2 nested models.
Using Support Vector Machine (SVM) for Regression.
Using Support Vector Machine (SVM) for Classification.
Manually calculate multiple regression.
Fitting polynomial regression in R is easy.
Sometimes a polynomial regression gives a better result than a linear regression
Covariance and Correlation are other fundamental concepts.
These basic calculations are the building blocks of advanced machine learning methods.