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data science template

in this repo u can look at default template for ds/ml/dl/.. projects or similar

how to use

[0] before creating a new project from this template, u need to install the next dependencies

  • cookiecutter

    $ brew install -U cookiecutter
    # or
    $ pip install cookiecutter
  • github cli

    • mac os

      # install
      $ brew install github/gh/gh
      
      # upgrade
      $ brew update && brew upgrade gh
    • debian/ubuntu linux

      • download the .deb file from the releases page
      • sudo apt install git && sudo dpkg -i gh_*_linux_amd64.deb install the downloaded file

[1] after go to the directory where u want to create your project and run

cookiecutter gh:vtrokhymenko/dst

using the next project structure

├── LICENSE                         <- will be created if u choose
├── README.md                       <- the main readme
│
├── config                          <- often it's yaml-files with some parameters
│
├── 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
│   └── features                    <- another
│
├── docs                            <- a default sphinx project (see sphinx-doc.org for details)
│
├── experiments                     <- for any experiments
│
├── models                          <- trained & serialized models, model predictions, or model summaries
│
├── notebooks                       <- notebooks for research
│                                      naming convention is a number (for ordering), the creator's initials, and a short `-`
│                                      delimited description, eg `1.0-jqp-initial-data-exploration`
│
├── references                      <- data dictionaries, manuals, and all other explanatory materials
│
├── tests                           <- test for project
│
├── {{ cookiecutter.repo_name }}    <- source code
│   ├── __init__.py                 <- makes src a python module eg propose generate with `mkinit`
│   │
│   ├── data                        <- scripts to download or generate data
│   │
│   ├── models                      <- scripts to train models and then use trained models to make predictions
│   │
│   └── visualization               <- scripts to create exploratory and results oriented visualizations
│
├── .gitignore                      <- default for python
│
└── .pre-commit-config.yaml         <- custom pcc with `isort`, `pre-commit-hooks`, `flake8`, `black`

another similar templates

propose to use next tools

citation

@misc{dst,
  author = {viktor trokhymenko},
  title = {data science template},
  year = {2020},
  publisher = {github},
  howpublished = {\url{https://github.com/vtrokhymenko/dst}}
}

license

this project is licensed under the terms of the mit license. see the license file for details

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another custom data science template via cookiecutter

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