📊 Linear Regression Model

This repository demonstrates a simple Linear Regression model using Python, NumPy, Matplotlib, and scikit-learn. The notebook showcases the step-by-step process of creating a random dataset, fitting a linear model, and evaluating its performance using metrics like MSE and R² score.

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📁 Repository Details

• 📂 Repository Name: Linear_regression_model
• 👤 Author: osctoss
• 📘 Notebook File: Linear_Model.ipynb

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🧪 What's Inside?

1. Importing Essential Libraries
2. Generating a Random Dataset
3. Splitting Dataset into Training and Testing
4. Training a Linear Regression Model
5. Visualizing the Regression Line
6. Calculating Model Accuracy (MSE & R² Score)

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🚀 Quick Preview

🔗 View Notebook on GitHub
▶️ Open in Google Colab

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📌 Requirements

You can run this notebook locally with the following libraries installed:

pip install numpy matplotlib scikit-learn