Hyperparameter Tuning
Showing 11 of 11 projects
A composable, modular, and scalable machine learning toolkit for building AI platforms on Kubernetes.
An AutoML library for deep learning that automates model selection and hyperparameter tuning using Keras and TensorFlow.
A Python package for constrained global optimization using Bayesian inference and Gaussian processes.
An automated machine learning toolkit that serves as a drop-in replacement for scikit-learn estimators.
A Python library offering scalable and user-friendly implementations of state-of-the-art neural forecasting models.
An open-source platform for building, training, and monitoring large-scale deep learning applications with full lifecycle MLOps.
An Automated Machine Learning Python package for tabular data with feature engineering, hyperparameter tuning, explanations, and automatic documentation.
An open-source machine learning platform for distributed training, hyperparameter tuning, experiment tracking, and resource management.
A Julia machine learning framework providing a unified interface and meta-algorithms for over 200 models.
A unified interface and infrastructure for machine learning in R, supporting classification, regression, clustering, and survival analysis.
A Bayesian optimization software package for automatically running experiments to minimize an objective in as few runs as possible.
Related Tags
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.