🧠 Machine Learning Algorithms Collection

A curated collection of fundamental Machine Learning algorithms implemented in Python.
This repository focuses on learning and understanding the core concepts behind classical ML models through simple and clear implementations.

---

📌 Overview

This repository contains implementations of widely used Machine Learning algorithms across different categories:

• Supervised Learning
• Unsupervised Learning
• Regression
• Classification
• Clustering

Each algorithm is implemented in a clean and educational way to help understand the underlying logic and mathematics.

---

📊 Algorithms Included

📈 Regression Models

• Linear Regression
• Logistic Regression

🌳 Tree-Based Models

• Decision Tree
• Random Forest

🔍 Clustering Algorithms

• K-Means Clustering
• DBSCAN
• Mean Shift Clustering
• Hierarchical Clustering
• Gaussian Mixture Models (GMM)

---

📂 Project Structure

Linear-Regression.py
Logistic-Regression.py
Decision-Tree.py
Random-Forest.py
K-Means-Clustering.py
DBSCAN.py
Mean-Shift-Clustering.py
Hierarchical-Clustering.py
Gaussian-Mixture-Models-(GMM)-Clustring.py

Datasets/
└── diabetes.csv

---

🧪 Dataset

• Diabetes dataset (diabetes.csv)
  Used for testing and demonstrating model behavior in classification tasks.

---

🎯 Purpose of This Repository

• Understand how ML algorithms work internally
• Practice implementation from scratch
• Compare different clustering and regression methods
• Build strong foundations in Machine Learning

---

🛠 Technologies Used

• Python 🐍
• NumPy
• Pandas
• Matplotlib
• Scikit-learn (for reference/comparison)

---

📈 Future Improvements

• Add data visualizations for each algorithm
• Add performance comparison charts
• Convert scripts into Jupyter Notebooks
• Improve documentation per algorithm
• Add hyperparameter tuning examples

---

👨‍💻 Author

Developed by Sam Afzali
Software, Web & AI Developer from Iran

🌐 Portfolio: https://samafzali.ir

🚀 Getting Started

Clone this repository:

git clone https://github.com/samafzali11/Machine-Learning.git
cd Machine-Learning