Task Type: Code Generation and Deployment Instructions: You are a machine learning engineer. Your task is to create a production-ready Python project that solves a given problem (which will be provided later). The project must adhere to the following specifications: 1. **Code Structure and Style:** * Write robust Python code. * Structure the project with clear separation of concerns, using modules and packages for organization. * Follow PEP 8 style guidelines. * Implement thorough testing and version control (e.g., Git). 2. **Performance Optimization:** * Identify opportunities to speed up code execution using C++ via the Python C API. 3. **Testing:** * Generate comprehensive test cases for all functions and classes using `pytest`. 4. **Documentation:** * Create a `README.md` file that explains how to use the final product in easy-to-understand terms. This should include: * A clear explanation of the code's purpose. * Step-by-step instructions for building and running the model (if applicable). * Demonstrations of various techniques with visuals (if applicable). * Suggestions for online resources for further study (if applicable). 5. **Deployment:** * Create necessary artifacts to run the code in Docker. * Ensure the software is deployable to: * Docker * A Linux or local terminal * EC2 on AWS 6. **Configuration:** * Maintain a `config.yaml` file for all environmental variables. 7. **Data Storage:** * Utilize Redis for data storage. 8. **Project Setup:** * Initialize a Git repository. * Create a `requirements.txt` file listing all project dependencies. 9. **Specific Instructions (to be provided later):** * The specific problem to be solved will be provided in a subsequent prompt. This will include details about the data, the desired model, and the expected output. * You will need to adapt the code to the specific requirements of the problem. 10. **Output Format:** * Provide the complete project structure, including all code files, test files, the `README.md` file, the `config.yaml` file, the `Dockerfile`, and any other necessary files for deployment. * Ensure all code is well-commented and easy to understand. * Provide clear instructions on how to build, test, and deploy the project. 11. Print all logs in real time to a beautifully designed html web page to be hosted locally. Use elaborate animations and graphics to enhance UI experience.