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Data Science Project Structure
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├── README.md <- The top-level README for developers using this project. | |
├── data | |
│ ├── external <- Data from third party sources. | |
│ ├── interim <- Intermediate data that has been transformed. | |
│ ├── processed <- The final, canonical data sets for modeling. | |
│ └── raw <- The original, immutable data dump. | |
│ | |
├── models <- Trained and serialized models, model predictions, or model summaries | |
│ | |
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering), | |
│ the creator's initials, and a short `-` delimited description, e.g. | |
│ `1.0-jqp-initial-data-exploration`. | |
│ | |
├── references <- Data dictionaries, manuals, and all other explanatory materials. | |
│ | |
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc. | |
│ └── figures <- Generated graphics and figures to be used in reporting | |
│ | |
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g. | |
│ generated with `pip freeze > requirements.txt` | |
│ | |
├── src <- Source code for use in this project. | |
│ ├── __init__.py <- Makes src a Python module | |
│ │ | |
│ ├── data <- Scripts to download or generate data | |
│ │ └── make_dataset.py | |
│ │ | |
│ ├── features <- Scripts to turn raw data into features for modeling | |
│ │ └── build_features.py | |
│ │ | |
│ ├── models <- Scripts to train models and then use trained models to make | |
│ │ │ predictions | |
│ │ ├── predict_model.py | |
│ │ └── train_model.py | |
│ │ | |
│ └── visualization <- Scripts to create exploratory and results oriented visualizations | |
│ └── visualize.py | |
│ |
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