Linear Regression from Scratch in Python

This project implements a Linear Regression algorithm from scratch using Python, without relying on any machine learning libraries like Scikit-Learn or TensorFlow.

Dataset: Kaggle

🚀 Features

• Implements Ordinary Least Squares (OLS) regression
• Supports Gradient Descent optimization
• Uses Manually Computed R² Score for model evaluation
• Handles only one feature (Univariate Regression)
• Built using only NumPy for matrix operations

📂 Project Structure

📁 linear_regression_scratch
│── linear_regression.ipynb     # Implementation Code of Linear Regression
│── Salary_Data.csv             # Dataset
│── README.md                   # Project documentation

📖 Learning Outcomes

• Understanding the math behind Linear Regression
• Implementing Gradient Descent Optimization
• Working with NumPy for vectorized operations
• Training a regression model without ML libraries