This page lists all of the machine learning tutorials available on Statology.

**Introduction to Machine Learning**

**Supervised vs. Unsupervised Learning
Regression vs. Classification Algorithms
The Bias-Variance Tradeoff**

**Linear Regression**

**Simple Linear Regression** (R, Python)

**Multiple Linear Regression** (R, Python)

**Classification**

**Logistic Regression** (R, Python)

**Linear Discriminant Analysis **(R, Python)

**Quadratic Discriminant Analysis** (R, Python)

**How to Assess Model Fit**

**What is Overfitting?
Leave-One-Out Cross-Validation** (R, Python)

**K-Fold Cross-Validation**(R, Python)

**Model Selection
Best Subset Selection
Stepwise Selection **(R)

**Regularization**

**Ridge Regression** (R, Python)

**Lasso Regression **(R, Python)

**Dimension Reduction
Principal Components Regression **(R, Python)

**Partial Least Squares**(R, Python)

**Advanced Regression Models
Polynomial Regression** (R, Python)

**Multivariate Adaptive Regression Splines**(R, Python)

**Tree-Based Methods**

**Classification and Regression Trees **(R)

**Bagging** (R)

**Random Forests** (R)

**Boosting** (R)

**Unsupervised Learning**

Principal Components Analysis in R

K-Means Clustering in R

K-Medoids Clustering in R

Hierarchical Clustering in R