Machine-Learning

Welcome to my Machine Learning Repository! This repository serves as a comprehensive resource for understanding different types of machine learning and provides practical example projects to help you grasp the concepts more effectively.

Table of Contents

Introduction

This repository is a collection of example projects, and some my projects that cover all major types of machine learning.

Projects

1. Supervised Learning

   1. Supervised Learning Algorithm

   2. Regression Regression Notes

      1. Linear Regression
         • Linear Regression Algorithm
      2. Polynomial Regression
      3. Ridge Regression
      4. Lasso Regression

   3. Classification

      1. KNN
         • KNN algorithm
      2. Naive Bayes
         • Naive Bayes Classification
      3. Decision Trees
         • Decision Trees
      4. Random Forests
      5. Logistic Regression
      6. Neural Networks
2. Unsupervised Learning
   1. Clustering
      1. k-Means Clustering
         • K-Means Clustering
      2. Hierarchical Clustering
   2. Dimensionality Reduction
      1. Principal Component Analysis (PCA)
      2. t-Distributed Stochastic Neighbor Embedding (t-SNE)
      3. Autoencoders
   3. Anomaly Detection
3. Semi-Supervised Learning
4. Reinforcement Learning
   1. Value-Based Methods
   2. Policy-Based Methods
   3. Model-Based Methods
5. Self-Supervised Learning