ML.NET is an open source and cross-platform machine learning framework for .NET. - dotnet/machinelearning
MLflow: A Machine Learning Lifecycle Platform MLflow is an open-source platform, purpose-built to assist machine learning practitioners and teams in handling the complexities of the machine learning process. MLflow focuses on the full lifecycle for machine learning projects, ensuring that each phase is...
ML professionals, data scientists, and engineers can use it in their day-to-day workflows to train and deploy models and manage machine learning operations (MLOps). You can create a model in Machine Learning or use a model built from an open-source platform, such as PyTorch, TensorFlow, ...
You can create a model in Azure Machine Learning or use a model built from an open-source platform, such as Pytorch, TensorFlow, or scikit-learn. Machine Learning Ops support can help you monitor, retrain, and redeploy models.There are many advantages of...
Machine learning platforms facilitate machine learning from end to end, giving users the ability to manage the entire data lifecycle, from data ingestion to inference. A few essential processes a machine learning platform should enable: Data ingestion, providing users the ability to integrate and inge...
Look for a platform that comes with enterprise-level governance, security, and control that helps you protect your infrastructure. Bring your machine learning models to market faster Simplify the way you build and deploy models with no-code automated machine learning capabilities, open-source support...
In this paper, we provide an alternative solution that devises a MLOps platform with open source frameworks on any virtual resources. Our MLOps approach is driven by the development roles of machine learning models. The tool chain of our MLOps connects to the typical CI/CD workflow of ...
The Hugging Face Hub is a platform that enables collaborative open source machine learning (ML). The hub works as a central place where users can explore, experiment, collaborate, and build technology with machine learning. On the hub, you can find more than 140,000 models, 50,000 ML apps...
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Machine learning deployment has many challenges but the new Seldon Core intends to help with it's new open source platform for deploying machine learning models on Kubernetes.