# 💎 Diamond Price Prediction

This is an end-to-end Machine Learning project that predicts the price of a diamond based on features such as carat, cut, color, clarity, depth, and dimensions. It includes data preprocessing, model training, evaluation, and deployment via a Flask-based web app.


## 🚀 Features

- 📦 Data Ingestion & Train-Test Split
- 🧹 Data Preprocessing with Pipelines (Imputation, Encoding, Scaling)
- 🤖 Model Training with LinearRegression, Ridge, Lasso, ElasticNet
- 📈 R² Score-based model selection
- 💾 Pickle-based model saving/loading
- 🌐 Flask-based Web UI for Prediction
- 🎨 Stylish, Responsive Frontend using HTML & CSS



## 🔧 Setup Instructions



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### Step 1: Clone the repository

```bash
git clone https://github.com/anjha1/DiamondPricePrediction.git

cd diamond-price-prediction

Step 2: Create and activate virtual environment

python -m venv venv
venv\Scripts\activate  # For Windows

Step 3: Install dependencies

pip install -r requirements.txt

Step 4: Train the model

python -m src.pipelines.training_pipelines

Step 5: Run the Flask app

python app.py

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🧪 Input Features

• Carat
• Cut (Fair, Good, Very Good, Premium, Ideal)
• Color (J to D)
• Clarity (I1 to IF)
• Depth
• Table
• X, Y, Z (dimensions in mm)

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🌐 Web App

• Enter the diamond features
• Click "Predict"
• Get the estimated price instantly!

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📊 Best Model

• ✅ LinearRegression
• 🎯 R² Score: ~0.937 on test set

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📄 License

This project is built for educational purposes. Feel free to fork and customize.

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Made with ❤️ by Achhuta Nand Jha