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project_structure.txt 1.3 KB

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  1. ├── @Author : Zoumana Keita - Data Scientist
  2. ├── LICENSE
  3. ├── README.md <- The top-level README for developers using this project.
  4. ├── data <- The folder containing the origininal data
  5. │ ├── spam.csv
  6. ├── models <- Trained and serialized models, model predictions, or model summaries
  7. │ ├── spam_detector_model.pkl
  8. ├── vectors <- Trained and serialized vector
  9. │ ├── vectorizer.pkl
  10. ├── notebooks <- Jupyter notebooks folder.
  11. │ ├── Preprocess_Train.ipynb
  12. ├── docker <- folder containing the docker files
  13. │ ├── Dockerfile
  14. ├── packages <- The customized project packages containing utility functions
  15. │ ├── __init__.py
  16. │ ├── data_preprocessor.py
  17. │ └── model_trainer.py
  18. ├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
  19. │ generated with `pip freeze > requirements.txt`
  20. ├── train_model.py <- Script to train the model
  21. ├── app.py <- The final Rest API file
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