Shypd.aiThe largest open index of AI toolsKatib is an automated machine learning (AutoML) tool that runs on Kubernetes. It supports hyperparameter tuning, early stopping, and neural architecture search for various ML frameworks.
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Katib is a Kubernetes-native project designed for automated machine learning (AutoML), providing robust capabilities for hyperparameter tuning, early stopping, and neural architecture search. It is framework-agnostic, allowing users to tune hyperparameters for applications written in any language and supporting popular ML frameworks like TensorFlow, PyTorch, and XGBoost. Katib can execute training jobs using various Kubernetes Custom Resources, including Kubeflow Training Operator, Argo Workflows, and Tekton Pipelines. It offers a range of search algorithms such as Random Search, Bayesian Optimization, TPE, and CMA-ES, and integrates with frameworks like Goptuna, Hyperopt, and Optuna. A Python SDK is available to simplify the creation of hyperparameter tuning jobs for data scientists.
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