nosa-autostreamlit 0.1.2

Automated Machine Learning and Data Visualization Framework

Nosa-autoStreamlit 🚀

📊 Automated Machine Learning and Data Visualization Framework

Nosa-autoStreamlit is an advanced Python framework that automates the creation of machine learning and data visualization Streamlit applications. Designed to simplify complex data science workflows with powerful, user-friendly tools.

✨ Features

🤖 Machine Learning Generator

• Supports classification and regression problems
• Advanced preprocessing techniques
• Multiple machine learning models
• Cross-validation
• Hyperparameter tuning
• Model saving and loading

📈 Data Visualization Generator

• Multiple visualization types
• Interactive Plotly plots
• Easy-to-use interface

🚀 Quick Start

Installation

Install via pip

pip install nosa-autostreamlit

Install from GitHub

pip install git+https://github.com/thesnak/nosa-autostreamlit.git

Local Installation

# Clone the repository
git clone https://github.com/yourusername/nosa-autostreamlit.git
cd nosa-autostreamlit

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

# Install dependencies
pip install -r requirements.txt

🔗 Links

• PyPI Package: https://pypi.org/project/nosa-autostreamlit/
• GitHub Repository: https://github.com/thesnak/nosa-autostreamlit

Machine Learning Example

from nosa_autostreamlit.generators import AdvancedMachineLearningGenerator

# Create generator
generator = AdvancedMachineLearningGenerator()

# Load data
generator.load_data(
    data, 
    target_column='target', 
    problem_type='classification'
)

# Preprocess and train models
generator.advanced_preprocessing()
generator.train_multiple_models()
generator.generate_model_comparison_report()

Data Visualization Example

from nosa_autostreamlit.generators import DataVisualizationGenerator

# Create generator
generator = DataVisualizationGenerator()

# Load data
generator.load_data(data)

# Create visualizations
generator.create_histogram()
generator.create_scatterplot()
generator.create_boxplot()

🛠 Key Components

• machine_learning_generator.py: Core ML functionality
• data_visualization_generator.py: Visualization tools
• advanced_ml_comparison.py: Example ML workflow
• advanced_data_viz_example.py: Example visualization workflow

📦 Dependencies

• Streamlit
• Pandas
• NumPy
• Scikit-learn
• Plotly
• Joblib

🤝 Contributing

Contributions are welcome! Please follow these steps:

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

📄 License

Distributed under the MIT License. See LICENSE for more information.

📞 Contact

Your Name - [e-mail]

Project Link: https://github.com/thesnak/nosa-autostreamlit

Made with ❤️ by Mohamed Mahmoud