{"id":28745446,"url":"https://github.com/tryomar/ai-search-algorithms","last_synced_at":"2025-10-28T19:06:17.287Z","repository":{"id":271470037,"uuid":"773527183","full_name":"TryOmar/AI-Search-Algorithms","owner":"TryOmar","description":"A comprehensive collection of AI algorithms including search algorithms, machine learning implementations, and game AI solutions in Python. 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This repository serves as both a learning resource and a practical reference for various AI/ML techniques.\n\n[![Python](https://img.shields.io/badge/Python-3.x-blue.svg)](https://www.python.org/)\n[![License](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)\n[![Author](https://img.shields.io/badge/Author-Omar7001--B-orange.svg)](https://github.com/Omar7001-B)\n\n## 🗂️ Project Structure\n\n### 1. Search Algorithms\n#### Informed Search `/Informed Search Algorithms/`\n- A* Search\n- Greedy Best-First Search\n\n#### Uninformed Search `/Uninformed Search Algorithms/`\n- Breadth-First Search (BFS)\n- Depth-First Search (DFS)\n- Depth-Limited Search (DLS)\n- Iterative Deepening DFS (IDDFS)\n- Uniform Cost Search (UCS)\n- Dijkstra's Algorithm\n\n### 2. Machine Learning `/MachineLearning/`\n- Naive Bayes Classifier\n- Object Detection System\n\n### 3. Games and Puzzles `/Games/`\n- Tic-Tac-Toe (Minimax)\n- 8-Puzzle (A*)\n- N-Queens (Genetic Algorithm)\n\n## 🚀 Getting Started\n\n### Prerequisites\n- Python 3.x\n- Required packages (varies by implementation)\n\n### Installation\n1. Clone the repository\n```bash\ngit clone https://github.com/Omar7001-B/AI-Search-Algorithms.git\ncd AI-Search-Algorithms\n```\n\n2. Install required packages for specific implementations\n```bash\n# For Machine Learning implementations\npip install numpy pandas scikit-learn\n\n# For Object Detection\npip install opencv-python tensorflow\n```\n\n## 📚 Documentation\nEach algorithm implementation includes:\n- Detailed README explaining the algorithm\n- Implementation details and complexity analysis\n- Usage instructions and examples\n- Requirements and dependencies\n\n## 🎯 Use Cases\n- **Search Algorithms**: Path finding, puzzle solving, optimization\n- **Machine Learning**: Text classification, object detection, pattern recognition\n- **Games**: AI opponents, puzzle solvers, optimization problems\n\n## 🛠️ Implementation Details\n- Clean, well-documented code\n- Efficient implementations\n- Practical examples and use cases\n- Performance optimizations\n\n## 📊 Performance\n- Search algorithms optimized for various scenarios\n- ML implementations with good accuracy-speed trade-offs\n- Game AI with intelligent decision making\n\n## 🤝 Contributing\nContributions are welcome! Please feel free to submit a Pull Request.\n\n1. Fork the repository\n2. Create your feature branch\n3. Commit your changes\n4. Push to the branch\n5. Open a Pull Request\n\n## 📝 License\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## 🙏 Acknowledgments\n- Thanks to all contributors\n- Inspired by classic AI/ML algorithms\n- Built with modern Python practices\n\n## 📧 Contact\n- GitHub: [@Omar7001-B](https://github.com/Omar7001-B)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftryomar%2Fai-search-algorithms","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftryomar%2Fai-search-algorithms","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftryomar%2Fai-search-algorithms/lists"}