yaml-ml 1.0.0

Your whole ML pipeline in one YAML file.

yaml-ML

yaml_ml streamlines machine learning workflows by letting you define data preprocessing, model training, and evaluation in one YAML file. Automate your ML pipeline with minimal code.

Have a look at the GitHub repo for detailed description and usage examples: yaml-ML.

1. Installation

Create a virtual environment (e.g. with conda), activate it and upgrade pip:

conda create --name yaml_ml_env
conda activate yaml_ml_env
pip install --upgrade pip

Then install the package:

pip install yaml-ml

2. Usage

With one configuration file

First, create a YAML configuration file: see docs. Then, after having activated the environment where yaml_ml is installed, run the command:

python -m yaml_ml --cfg path/to/your/config/yaml/file

With multiple configuration files

In case you want to test different configurations, create corresponding YAML files and put them in a unique folder. To launch all the corresponding pipelines in parallel using multiprocessing with N worker processes, run the command:

python -m yaml_ml --cfg path/to/your/configs/folder --n_processes N 

N.B: Without providing the --n_processes argument, pipelines will be launched sequentially.