Machine Learning Repository

This repository contains code and examples for various machine learning tasks.

Table of Contents

• Ensemble Learning
• Classification
• Regression
• Feature Engineering
• Hyperparameter Tuning
• Clustering

Ensemble Learning

This folder contains examples and implementations of ensemble learning methods, including:

• Bagging
• Boosting
• Voting
• Random forests

Classification

This folder contains examples and implementations of classification algorithms, including:

• Logistic regression
• Decision trees
• Support vector machines
• Naive Bayes
• k-Nearest Neighbors
• Random Forests

Regression

This folder contains examples and implementations of regression algorithms, including:

• Linear regression
• Ridge regression
• Lasso regression
• ElasticNet regression
• Support Vector Machine
• Stochastic Gradient Descent
• Random Forest Regression

Feature Engineering

This folder contains examples and implementations of feature engineering techniques, including:

• Feature scaling and normalization
• Principal component analysis (PCA)
• t-SNE
• Feature selection

Hyperparameter Tuning

This folder contains examples and implementations of hyperparameter tuning methods, including:

• Grid search
• Random search
• Bayesian optimization

Clustering

This folder contains examples and implementations of clustering algorithms, including:

• k-Means
• Hierarchical clustering
• DBSCAN
• Gaussian mixture models