cookiecutter-data-science and template-starter
These are complements: cookiecutter-data-science provides a general project directory structure and workflow organization, while ZenML's template builds on top of that foundation to add ML pipeline orchestration and experiment tracking capabilities.
About cookiecutter-data-science
drivendataorg/cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Built on the [cookiecutter](https://cookiecutter.readthedocs.io/) templating framework, it provides a Python package (`ccds` CLI) that scaffolds projects with standardized directories for data pipelines, notebooks, models, and documentation, along with `pyproject.toml` and Makefile conventions for reproducibility. The template separates raw/processed data, intermediate artifacts, and source code into a modular Python package structure with dedicated modules for dataset handling, feature engineering, and model training/inference.
About template-starter
zenml-io/template-starter
A template for a starter project for ZenML
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work