🏠 House Price Prediction using Machine Learning

📌 Project Overview

This project predicts house prices based on:

• Area (Square Feet)
• Number of Bedrooms
• Number of Bathrooms

The model is built using Multiple Linear Regression.

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🛠 Technologies Used

• Python
• Pandas
• NumPy
• Scikit-learn

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📊 Machine Learning Algorithm

• Multiple Linear Regression

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⚙️ Project Workflow

1. Load Dataset
2. Data Preprocessing
3. Train-Test Split
4. Model Training
5. Model Evaluation
6. Price Prediction

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📈 Model Evaluation Metrics

• Mean Squared Error (MSE)
• R2 Score

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🚀 How to Run

1. Install dependencies:

pip install -r requirements.txt

2. Run the model:

python house_price_model.py

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🎯 Learning Outcome

• Understanding Regression Models
• Data Splitting
• Model Evaluation
• Real-world Price Prediction