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This repo is a Starting Pack for DS projects. You can rearrange the structure to make it fits your project.

Project Organization

├── LICENSE
├── README.md          <- The top-level README for developers using this project.
├── data               <- Should be in your computer but not on Github (only in .gitignore)
│   ├── 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 name, and a short `-` delimited description, e.g.
│                         `1.0-alban-data-exploration`.
│
├── references         <- Data dictionaries, manuals, links, and all other explanatory materials.
│
├── reports            <- The reports that you'll make during this project as PDF
│   └── 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
│   │
│   ├── 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

Project based on the cookiecutter data science project template. #cookiecutterdatascience

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