Showing 8 of 8 projects
An open-source, low-code Python library that automates end-to-end machine learning workflows.
An easy-to-use, scalable hyperparameter optimization framework for Keras models with define-by-run syntax and built-in search algorithms.
Hyperopt-sklearn automates hyperparameter optimization and model selection for scikit-learn machine learning pipelines.
A Python library for automated hyperparameter optimization and model evaluation with TensorFlow, Keras, and PyTorch.
Implementation of hyperparameter optimization methods for ML/DL models with sample code for regression and classification tasks.
A web-based tool for automated hyperparameter tuning and stacked ensemble creation in Python.
An intelligent data search and enrichment library for machine learning that automatically finds and adds relevant external features to ML pipelines.
A fast feature selection algorithm for tree-based models like XGBoost, designed to outperform Boruta in speed and performance.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.