{"id":22282831,"url":"https://github.com/ahammadnafiz/predicta","last_synced_at":"2025-07-28T21:32:04.352Z","repository":{"id":238713696,"uuid":"791446167","full_name":"ahammadnafiz/Predicta","owner":"ahammadnafiz","description":"Predicta: Simplify your workflow with our powerful data analysis and machine learning 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align=\"center\"\u003e\r\n   \u003ca href=\"https://www.python.org/\"\u003e\r\n      \u003cimg src=\"https://img.shields.io/badge/python-v3.8+-blue.svg\" alt=\"Python\"\u003e\r\n   \u003c/a\u003e\r\n   \u003ca href=\"https://opensource.org/licenses/MIT\"\u003e\r\n      \u003cimg src=\"https://img.shields.io/badge/license-MIT-green.svg\" alt=\"License\"\u003e\r\n   \u003c/a\u003e\r\n   \u003ca href=\"https://streamlit.io\"\u003e\r\n      \u003cimg src=\"https://static.streamlit.io/badges/streamlit_badge_black_white.svg\" alt=\"Streamlit\"\u003e\r\n   \u003c/a\u003e\r\n   \u003ca href=\"https://github.com/ahammadnafiz/Predicta/issues\"\u003e\r\n      \u003cimg src=\"https://img.shields.io/github/issues/ahammadnafiz/Predicta\" alt=\"GitHub Issues\"\u003e\r\n   \u003c/a\u003e\r\n   \u003ca href=\"https://github.com/ahammadnafiz/Predicta/stargazers\"\u003e\r\n      \u003cimg src=\"https://img.shields.io/github/stars/ahammadnafiz/Predicta\" alt=\"GitHub Stars\"\u003e\r\n   \u003c/a\u003e\r\n   \u003ca href=\"https://pypi.org/project/predicta/\"\u003e\r\n      \u003cimg src=\"https://img.shields.io/badge/package-professional-orange.svg\" alt=\"Professional Package\"\u003e\r\n   \u003c/a\u003e\r\n\u003c/p\u003e\r\n\r\n\u003cp align=\"center\"\u003e\r\n  \u003ca href=\"https://www.python.org\" target=\"_blank\"\u003e\r\n    \u003cimg src=\"https://raw.githubusercontent.com/devicons/devicon/master/icons/python/python-original.svg\" alt=\"python\" width=\"40\" height=\"40\"/\u003e\r\n  \u003c/a\u003e\r\n  \u003ca href=\"https://streamlit.io\" target=\"_blank\"\u003e\r\n    \u003cimg src=\"https://streamlit.io/images/brand/streamlit-mark-color.svg\" alt=\"streamlit\" width=\"40\" height=\"40\"/\u003e\r\n  \u003c/a\u003e\r\n  \u003ca href=\"https://scikit-learn.org/\" target=\"_blank\"\u003e\r\n    \u003cimg src=\"https://upload.wikimedia.org/wikipedia/commons/0/05/Scikit_learn_logo_small.svg\" alt=\"scikit_learn\" width=\"40\" height=\"40\"/\u003e\r\n  \u003c/a\u003e\r\n  \u003ca href=\"https://pytorch.org/\" target=\"_blank\"\u003e\r\n    \u003cimg src=\"https://www.vectorlogo.zone/logos/pytorch/pytorch-icon.svg\" alt=\"pytorch\" width=\"40\" height=\"40\"/\u003e\r\n  \u003c/a\u003e\r\n\u003c/p\u003e\r\n\r\n\r\n\u003e 🚀 Professional Machine Learning Platform for End-to-End Data Science Workflows\r\n\r\nPredicta is a comprehensive, enterprise-grade machine learning platform that transforms complex data science workflows into intuitive, streamlined processes. Built with a modular architecture and professional coding standards, Predicta empowers data scientists to build, deploy, and maintain robust predictive models efficiently.\r\n\r\n**🎯 Now featuring professional package structure with CLI interface, centralized configuration, and modular architecture!**\r\n\r\n![Predicta Dashboard](predicta/assets/predictaapp_streamlitapp.jpeg)\r\n\r\n## ✨ Features\r\n\r\n### 📊 Advanced Data Analysis\r\n- **Interactive Visualization Suite**: Generate insightful plots and charts\r\n- **Automated Data Profiling**: Quick statistical summaries and data quality checks\r\n- **Pattern Recognition**: Identify correlations and trends effortlessly\r\n- **Missing Data Detection**: Smart identification of data gaps and anomalies\r\n\r\n### 🔧 Intelligent Preprocessing\r\n- **Automated Data Cleaning**: Smart handling of missing values and outliers\r\n- **Feature Engineering**: Advanced encoding and scaling techniques\r\n- **Data Validation**: Robust checks for data integrity and consistency\r\n- **Type Inference**: Automatic detection and conversion of data types\r\n\r\n### 🤖 Machine Learning Pipeline\r\n- **Algorithm Selection**: Curated collection of ML algorithms for various tasks\r\n- **Hyperparameter Optimization**: Automated model tuning for optimal performance\r\n- **Cross-Validation**: Robust model validation techniques\r\n- **Performance Metrics**: Comprehensive model evaluation suite\r\n\r\n### 📈 Production-Ready Features\r\n- **Model Export**: Easy deployment of trained models\r\n- **Batch Prediction**: Efficient processing of large datasets\r\n- **API Integration**: RESTful API for seamless integration\r\n- **Version Control**: Track model versions and experiments\r\n\r\n### 🏗️ Professional Package Features\r\n- **CLI Interface**: Command-line tools for easy management\r\n- **Modular Architecture**: Self-contained, reusable components\r\n- **Centralized Configuration**: Professional settings management\r\n- **Advanced Logging**: Comprehensive logging with error filtering\r\n- **Asset Management**: Proper handling of static resources\r\n- **Session Management**: Robust temporary file handling\r\n- **Import System**: Professional absolute import structure\r\n- **Package Installation**: Standard pip-installable package\r\n\r\n## 🚀 Quick Start\r\n\r\n### Prerequisites\r\n- Python 3.8+\r\n- pip package manager\r\n\r\n### Installation\r\n\r\n1. Clone the repository:\r\n```bash\r\ngit clone https://github.com/ahammadnafiz/Predicta.git\r\ncd Predicta\r\n```\r\n\r\n2. Create a virtual environment (recommended):\r\n```bash\r\npython -m venv venv\r\nsource venv/bin/activate  # Linux/Mac\r\n# or\r\n.\\venv\\Scripts\\activate  # Windows\r\n```\r\n\r\n3. Install the package:\r\n```bash\r\npip install -e .\r\n```\r\n\r\n### Usage\r\n\r\n#### Command Line Interface\r\n```bash\r\n# Launch the Streamlit application\r\npredicta run\r\n\r\n# Check version\r\npredicta version\r\n\r\n# View configuration\r\npredicta config\r\n\r\n# Clean temporary files\r\npredicta clean\r\n```\r\n\r\n#### Direct Python Usage\r\n```bash\r\n# Launch Streamlit application directly\r\npython -m predicta.app.main\r\n\r\n# Or using streamlit\r\nstreamlit run predicta/app/main.py\r\n```\r\n\r\n## 📁 Project Structure\r\n\r\n```\r\npredicta/\r\n├── __init__.py                    # Package initialization\r\n├── cli.py                         # Command-line interface\r\n├── app/                           # Main application\r\n│   ├── __init__.py\r\n│   ├── main.py                    # Streamlit app entry point\r\n│   ├── predicta_app.py           # Core application logic\r\n│   └── pages/                     # Streamlit pages\r\n│       ├── predicta_chat.py\r\n│       ├── predicta_viz.py\r\n│       └── prediction_app.py\r\n├── core/                          # Core infrastructure\r\n│   ├── __init__.py\r\n│   ├── config.py                  # Configuration management\r\n│   ├── logging_config.py          # Logging setup\r\n│   └── streamlit_patches.py       # Compatibility patches\r\n├── modules/                       # Feature modules\r\n│   ├── data_exploration/          # Data analysis and visualization\r\n│   ├── feature_cleaning/          # Data cleaning and preprocessing\r\n│   ├── feature_engineering/       # Feature transformation\r\n│   ├── feature_selection/         # Feature importance and selection\r\n│   ├── ml_models/                 # Machine learning algorithms\r\n│   └── code_editor/               # Code editing capabilities\r\n├── ui/                            # User interface components\r\n│   └── theme/                     # Theming and styling\r\n├── utils/                         # Utility functions\r\n└── assets/                        # Static assets (images, etc.)\r\n```\r\n\r\n## 🏗️ Architecture\r\n\r\nPredicta follows a modular architecture with clear separation of concerns:\r\n\r\n- **Core**: Infrastructure components (config, logging, patches)\r\n- **Modules**: Self-contained feature modules with specific responsibilities\r\n- **UI**: User interface components and theming\r\n- **App**: Main application logic and Streamlit pages\r\n- **CLI**: Command-line interface for easy launching and management\r\n\r\n## 🤝 Contributing\r\n\r\nWe love your input! Contribute to Predicta in many ways:\r\n\r\n1. Report bugs and feature requests\r\n2. Review source code changes\r\n3. Submit pull requests\r\n4. Help others in discussions\r\n\r\nCheck out our [Contributing Guidelines](CONTRIBUTING.md) for more details.\r\n\r\n### Development Setup\r\n\r\n1. Clone and install in development mode:\r\n```bash\r\ngit clone https://github.com/ahammadnafiz/Predicta.git\r\ncd Predicta\r\npip install -e .\r\n```\r\n\r\n2. Install development dependencies:\r\n```bash\r\npip install -r requirements.txt\r\n```\r\n\r\n3. Run tests (when available):\r\n```bash\r\npython -m pytest tests/\r\n```\r\n\r\n## 🔧 Configuration\r\n\r\nPredicta uses a centralized configuration system:\r\n\r\n- **Config Management**: Centralized settings in `predicta/core/config.py`\r\n- **Logging**: Professional logging setup with configurable levels\r\n- **Asset Management**: Centralized asset path management\r\n- **Session Management**: Temporary file handling and cleanup\r\n\r\n## 📦 Package Features\r\n\r\n- **Professional Structure**: Follows Python packaging best practices\r\n- **Modular Design**: Self-contained modules with clear interfaces\r\n- **CLI Interface**: Easy command-line access to all features\r\n- **Logging System**: Comprehensive logging with PyTorch compatibility\r\n- **Configuration Management**: Centralized settings and path management\r\n- **Asset Management**: Proper handling of static assets and resources\r\n\r\n## 🗺️ Roadmap\r\n\r\n- [ ] Deep Learning Integration\r\n- [ ] AutoML Capabilities\r\n- [ ] Time Series Analysis\r\n- [ ] Natural Language Processing\r\n- [ ] Cloud Deployment Options\r\n- [ ] Real-time Processing\r\n\r\n## 📄 License\r\n\r\nThis project is licensed under the Apache License - see the [LICENSE](https://github.com/ahammadnafiz/Predicta/blob/main/LICENSE) file for details.\r\n\r\n## 🌟 Support\r\n\r\n⭐️ Star this repo if you find it helpful!\r\n\r\n## 📧 Contact\r\n\r\nGot questions? Reach out!\r\n\r\n- Email: ahammadnafiz@outlook.com\r\n\r\n---\r\n\r\n\u003cp align=\"center\"\u003eMade with ❤️ by Ahammad Nafiz\u003c/p\u003e","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahammadnafiz%2Fpredicta","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fahammadnafiz%2Fpredicta","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahammadnafiz%2Fpredicta/lists"}