cookiecutter-data-science and cookie-ml

These are competitors—both provide cookiecutter templates for standardizing ML project structure, but A is a mature, widely-adopted standard while B is an abandoned alternative attempting to solve the same initialization problem.

cookie-ml
30
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 25/25
Community 25/25
Maintenance 13/25
Adoption 1/25
Maturity 16/25
Community 0/25
Stars: 9,723
Forks: 2,628
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 1
Forks:
Downloads:
Commits (30d): 0
Language: Python
License: GPL-3.0
No risk flags
No Package No Dependents

About cookiecutter-data-science

drivendataorg/cookiecutter-data-science

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

Setting up a data science project can be complex, with many files and folders to organize. This tool helps data scientists quickly create a standardized, logical structure for new projects, providing a consistent layout for raw data, processed data, notebooks, models, and reports right from the start. It ensures all team members can easily understand and navigate the project's layout.

data-science-project-management data-organization ml-project-setup research-workflow data-pipeline-structure

About cookie-ml

rvbug/cookie-ml

Helps to generate ML cookiecutter structure using Python

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