Machine Learning

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

These basic calculations are the building blocks of advanced machine learning methods.