{"id":16269744,"url":"https://github.com/simonbernarding/ml_project_simonbernarding","last_synced_at":"2025-10-12T14:53:22.457Z","repository":{"id":254983053,"uuid":"827800329","full_name":"SimonBernarding/ML_project_SimonBernarding","owner":"SimonBernarding","description":"This project focuses on predicting flight delays using historical data from a Tunisian airline. 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Make sure to have streamlit installed in your directory, as described in the requirements. \n\n     ```BASH\n    streamlit run app.py\n    ```\n    After that a local host is started in your standard browser. \n \n\n\n## Set up your Environment\n\n\n\n### **`macOS`** type the following commands : \n\n- For installing the virtual environment you can either use the [Makefile](Makefile) and run `make setup` or install it manually with the following commands:\n\n     ```BASH\n    make setup\n    ```\n    After that active your environment by following commands:\n    ```BASH\n    source .venv/bin/activate\n    ```\nOr ....\n- Install the virtual environment and the required packages by following commands:\n\n    ```BASH\n    pyenv local 3.11.3\n    python -m venv .venv\n    source .venv/bin/activate\n    pip install --upgrade pip\n    pip install -r requirements.txt\n    ```\n    \n### **`WindowsOS`** type the following commands :\n\n- Install the virtual environment and the required packages by following commands.\n\n   For `PowerShell` CLI :\n\n    ```PowerShell\n    pyenv local 3.11.3\n    python -m venv .venv\n    .venv\\Scripts\\Activate.ps1\n    pip install --upgrade pip\n    pip install -r requirements.txt\n    ```\n\n    For `Git-bash` CLI :\n  \n    ```BASH\n    pyenv local 3.11.3\n    python -m venv .venv\n    source .venv/Scripts/activate\n    pip install --upgrade pip\n    pip install -r requirements.txt\n    ```\n\n    **`Note:`**\n    If you encounter an error when trying to run `pip install --upgrade pip`, try using the following command:\n    ```Bash\n    python.exe -m pip install --upgrade pip\n    ```\n\n\n   \n## Usage\n\nIn order to train the model and store test data in the data folder and the model in models run:\n\n**`Note`**: Make sure your environment is activated.\n\n```bash\npython example_files/train.py  \n```\n\nIn order to test that predict works on a test set you created run:\n\n```bash\npython example_files/predict.py models/linear_regression_model.sav data/X_test.csv data/y_test.csv\n```\n\n## Limitations\n\nDevelopment libraries are part of the production environment, normally these would be separate as the production code should be as slim as possible.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsimonbernarding%2Fml_project_simonbernarding","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsimonbernarding%2Fml_project_simonbernarding","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsimonbernarding%2Fml_project_simonbernarding/lists"}