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--- |
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license: mit |
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title: Customer Purchase Prediction |
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sdk: gradio |
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emoji: 🚀 |
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colorFrom: blue |
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colorTo: green |
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short_description: Neural network demo for customer purchase prediction |
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--- |
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title: Customer Purchase Prediction |
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emoji: 🛒 |
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colorFrom: blue |
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colorTo: green |
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sdk: gradio |
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sdk_version: 4.0.0 |
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app_file: app.py |
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pinned: false |
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license: mit |
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--- |
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# Customer Purchase Prediction Neural Network |
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An interactive demo of a neural network that predicts customer purchase behavior based on website engagement metrics. |
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## 🎯 Features |
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- **Interactive Predictions**: Test different customer scenarios in real-time |
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- **Visual Analytics**: Beautiful charts and visualizations |
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- **Model Performance**: Comprehensive evaluation metrics |
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- **Customer Segmentation**: Analyze different user types |
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## 🧠 Model Details |
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- **Architecture**: Multi-layer Neural Network (32 → 16 → 8 neurons) |
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- **Features**: Visit Duration, Pages Visited |
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- **Framework**: scikit-learn MLPClassifier |
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- **Performance**: ~66% accuracy, 0.57 AUC |
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## 🚀 Try It Out |
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1. **Adjust the sliders** to set customer behavior parameters |
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2. **View real-time predictions** with probability scores |
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3. **Explore data visualizations** to understand patterns |
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4. **Check model performance** metrics and analysis |
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## 💼 Business Applications |
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- E-commerce optimization |
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- Marketing campaign targeting |
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- User experience enhancement |
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- Revenue forecasting |
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## 🔗 Links |
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- **Source Code**: [GitHub Repository](https://github.com/drbinna/customer-purchase-prediction) |
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- **Developer**: [@drbinna](https://github.com/drbinna) |
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Built with ❤️ using Gradio and scikit-learn |
