srinathh / cookiecutter-ml-devcontainer

Minimalist project template for reproducible machine learning a la https://drivendata.github.io/cookiecutter-data-science/ and https://blog.mariokrapp.com/Cookiecutter_for_a_more_transparent_and_reproducible_science.html

Reproducible ML for Minimalists

Pared-down project template for reproducible Machine Learning. Adopted from Cookiecutter Data Science and Mario Krapp

How to Use

1. First install cookiecutter:

pip install cookiecutter

2. Then initialise a template:

cookiecutter gh:jeannefukumaru/cookiecutter-ml

More information on the cookiecutter project can be found here

Template Structure

.
    ├── AUTHORS.md
    ├── LICENSE
    ├── README.md
    ├── models  <- compiled model .pkl or HDFS or .pb format
    ├── config  <- any configuration files
    ├── data
    │   ├── interim <- data in intermediate processing stage
    │   ├── processed <- data after all preprocessing has been done
    │   └── raw <- original unmodified data acting as source of truth and provenance
    ├── docs  <- usage documentation or reference papers
    ├── notebooks <- jupyter notebooks for exploratory analysis and explanation 
    ├── reports <- generated project artefacts eg. visualisations or tables
    │   └── figures
    └── src
        ├── data-proc <- scripts for processing data eg. transformations, dataset merges etc. 
        ├── viz  <- scripts for visualisation during EDA, modelling, error analysis etc. 
        ├── modeling    <- scripts for generating models
    |-- environment.yml . <- YAML file with libraries and library versions for recreating an environment