I recently released a Python package called vinzy-automl, a lightweight AutoML toolkit that lets you train, compare, and evaluate a wide range of machine-learning models with minimal code. It supports 60+ models (including XGBoost, LightGBM, and CatBoost), optional hyperparameter tuning, multithreaded training, performance metrics, and comparison visualizations. The goal is to simplify model selection and reduce repetitive ML boilerplate while still giving users the flexibility to customize models or parameter grids. You can install it via pip install vinzy_automl or pip install vinzy_automl[full], and I’d love feedback, suggestions, or ideas for improving it. Here’s the PyPI page if you want to check it out:

pypi: https://pypi.org/project/vinzy-automl/

github: https://github.com/vinayak-97/vinzy_automl