Getting Started

Installation

The python environment for the repository can be created using either conda or virtualenv, by running from the root of the repo:

Using conda

conda create --name=ml-fuel python=3.8
conda activate ml-fuel

Using virtualenv

python3 -m venv env
source env/bin/activate

Install dependencies

pip install -U pip
pip install -r requirements.txt

This includes all the packages required for running the code in the repository.

Pre-trained models

Pre-trained models are available:

• LightGBM.joblib at src/pre-trained_models/LightGBM.joblib

• CatBoost.joblib at src/pre-trained_models/CatBoost.joblib

Demo Notebooks

Notebooks for training and inference:

• LightGBM_training.ipynb at notebooks/LightGBM_training.ipynb

• LightGBM_inference.ipynb at notebooks/LightGBM_inference.ipynb

• CatBoost_training.ipynb at notebooks/CatBoost_training.ipynb

• CatBoost_inference.ipynb at notebooks/CatBoost_inference.ipynb