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📏 Height Prediction using Decision Tree (Streamlit Web App)

🚀 Project Overview

This project is a Machine Learning web application that predicts a person's height based on their age using a Decision Tree Regressor. The model is deployed using Streamlit with a modern and interactive UI.

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🎯 Features

• 📂 Upload your own dataset (CSV format)
• 🤖 Train Decision Tree model instantly
• 🎛️ Enter age and get height prediction
• 📊 Visualize model predictions with graph
• 📈 Performance metrics (RMSE & R2 Score)
• 🎨 Beautiful gradient UI (not basic black & white)

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🧠 Technologies Used

• Python 🐍
• Pandas
• NumPy
• Matplotlib
• Scikit-learn
• Streamlit

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📁 Project Structure

HeightPredictionDecisionTree/
│── app.py
│── dataset.csv
│── requirements.txt
│── README.md

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⚙️ Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/selvan-01/Height-Prediction-DecisionTree.git
cd HeightPredictionDecisionTree

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Run the Application

streamlit run app.py

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📊 How It Works

1. Upload your dataset (Age vs Height)
2. The model is trained using Decision Tree Regression
3. Enter an age value
4. Get predicted height instantly
5. View graph and performance metrics

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📸 Sample Output

• 📈 Graph showing prediction curve
• 📏 Predicted height based on age
• ✅ RMSE and R2 Score for accuracy

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🌟 Future Improvements

• Add multiple input features (weight, gender, etc.)
• Improve model accuracy with advanced algorithms
• Deploy app online (Streamlit Cloud / Vercel)
• Add download report option

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🔗 Links

• 💼 LinkedIn
• 🌍 Portfolio
• 💻 GitHub

🙌 Author

S. Senthamil Selvan (Sen) 🎯 Aspiring ML Developer | AI Enthusiast

🔗 Portfolio: https://senthamill.vercel.app/

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⭐ Support

If you like this project, give it a ⭐ on GitHub and share it!

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