Machine Learning Project Template

Requirements to use this template:

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• Python >= 3.6
• Cookiecutter Python package >= 1.4.0: This can be installed with pip by or conda depending on how you manage your Python packages:

$ pip install cookiecutter

or

$ conda config --add channels conda-forge
$ conda install cookiecutter

To start a new project, run:

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cookiecutter https://github.com/thanhtcptit/ml_project_template

The resulting directory structure

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The directory structure of your new project looks like this:

├── configs                     <- Store experiment config files
├── 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
├── train_logs                  <- Trained and serialized models, model predictions, or model summaries  
├── notebooks                   <- Jupyter notebooks
├── references                  <- Data dictionaries, manuals, and all other explanatory materials
├── reports                     <- Generated analysis as HTML, PDF, LaTeX, etc
├── resources                   <- Other resources for the project
├── src                         <- Source code for use in this project.
│   ├── data                    <- Scripts to download or generate data
│   ├── features                <- Scripts to turn raw data into features for modeling
│   ├── models                  <- Scripts to define models
│   ├── utils                   <- Scripts to define helper function
│   ├── visualization           <- Scripts to create exploratory and results oriented visualizations
│   ├── __init__.py
│   ├── evaluate.py
│   └── train.py
├── README.md                   <- The top-level README for developers using this project
├── requirements.txt            <- The requirements file for reproducing the analysis environment
├── run.py                      <- Script to run tasks 
└── setup.py                    <- Makes project pip installable (pip install -e .) so src can be imported

Installing development requirements

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pip install -r requirements.txt