🤖 AutoML-MLOps

Empowering Your Machine Learning Workflow

Your All-in-One Solution for Streamlined Model Development and Deployment

Features · Getting Started · Why AutoML-MLOps · Contributing

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✨ Features

Feature	Description
🚀 Automated Model Training	Upload your dataset and let AutoML-MLOps handle the rest
📊 Interactive Dashboard	Real-time monitoring of training progress and model performance
🎯 Smart Target Selection	Automatic detection or manual selection of your target column
📈 Comprehensive Metrics	In-depth model evaluation with detailed metrics and visualizations
💾 Efficient Model Management	Easy comparison and download of trained models
👁️ Data Visualization	Built-in CSV data preview and exploration tools

🚀 Getting Started

1️⃣ Upload Your Data

• Select the "Choose File" button
• Upload your CSV dataset
• Verify data preview

2️⃣ Configure Your Model

• Choose target column detection method:
  • Automatic detection
  • Manual selection
• Customize training parameters

3️⃣ Train Your Model

• Initiate training with one click
• Monitor real-time progress
• View live training metrics

4️⃣ Explore Results

• Analyze comprehensive model metrics
• Explore interactive visualizations
• Review performance indicators

5️⃣ Deploy Your Model

• Download trained model
• Access model artifacts
• Ready for production deployment

💡 Why AutoML-MLOps?

Benefit	Description
⏱️ Save Time	Automate repetitive tasks in the ML pipeline
📈 Improve Accuracy	Leverage advanced algorithms for optimal model selection
🔍 Gain Insights	Visualize your data and model performance like never before
🔄 Stay Flexible	Suitable for both beginners and experienced data scientists

🛠️ Technology Stack

Frontend

• React
• Next.js
• Tailwind CSS

Backend

• Python
• scikit-learn

Visualization

• Recharts

👥 Contributing

We value and welcome contributions from the community! Here's how you can contribute:

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

For major changes, please open an issue first to discuss what you would like to change.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Report Bug · Request Feature