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Published directory entries matching your search.
Hypernets is a general AutoML framework for building automatic optimization tools for machine learning frameworks and libraries, including tensorflow, keras, pytorch, sklearn, lightgbm and xgboost. It offers an abstract search space representation covering hyperparameter optimization and neural architecture search, with optimization algorithms such as evolution algorithm and Monte Carlo tree search.
Hyperopt is an open-source Python library available on GitHub, designed to provide distributed asynchronous hyperparameter optimization functionality for tuning machine learning models in development workflows, production environments, as well as research settings.
A delightful machine learning tool that allows you to train/fit, test and use models without writing code.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Indic LLM Arena provides machine-learning models, research, training resources, or evaluation tools.
Infer.NET is a framework for running Bayesian inference in graphical models. It can be used for machine learning problems such as classification, recommendation or clustering, and for probabilistic programming. It is published as open source on GitHub under the MIT license and available as NuGet packages.
InferKit provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Invicta provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
IUMB supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Autograd and XLA for high-performance machine learning research.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Julius provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
A JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.
An unsupervised machine learning extension library for NetworkX with a Scikit-Learn like API.
Kubeflow Katib is a Kubernetes-native project for automated machine learning (AutoML). It supports hyperparameter tuning, early stopping and neural architecture search, and is agnostic to machine learning frameworks, natively supporting frameworks such as TensorFlow, PyTorch and XGBoost. Training jobs can use any Kubernetes Custom Resources, with out-of-box support for Kubeflow Training Operator, Argo Workflows and Tekton Pipelines. A Python SDK simplifies creating tuning jobs.
Keepsake is a version control system for machine learning projects. It allows tracking changes to models, data, and experiments. It is developed by Replicate and hosted on GitHub as an open-source repository. The project is not actively maintained.
