tabular-ml 0.0.2

[](https://github.com/xaviernogueira/Tabular_ML/actions/workflows/pre-commit.yml) [](https://github.com/xaviernogueira/Tabular_ML/actions/workflows/tests.yml) [](https://codecov.io/gh/xaviernogueira/Tabular_ML)

# tabular_ml - tabular machine learning simplified! I’ve packaged and open sourced my personal machine learning tools to speed up your next data science project.

Train, evaluate, ensemble, and optimize hyperparameters from a standardized interface.


## Key Features * Train models efficiently without worrying about library differences! tabular_ml implements library specific, performance oriented, patterns/classes under-the-hood (i.e., xgboost.DMatrix -> xgboost.Booster). * Automate the K-Fold evaluation process across multiple models simultaneously (including ensembles). * Rapidly optimize hyperparameters using [optuna](https://optuna.org/). Leverage our built-in parameter search spaces, or adjust to your needs. * Plugin-able. Write your own plugins to extend functionality without forking (and consider contributing your plugins!).

For full documentation see our GitHub ReadMe [here](https://github.com/xaviernogueira/Tabular_ML).