Create a new ML workspace
Step‑by‑step guide to set up an Azure Machine Learning workspace using the portal, CLI, and SDK.
Step‑by‑step guide to set up an Azure Machine Learning workspace using the portal, CLI, and SDK.
Learn how to package, register, and deploy a trained model using Azure Container Instances or AKS.
Automate model selection and hyperparameter tuning with Azure Automated ML.
Integrate Azure Machine Learning with Azure DevOps for continuous integration and delivery.
Implement data drift detection, logging, and alerting for deployed models.
Best practices for storing, versioning, and retrieving features across projects.
Configure multi‑node GPU clusters for large‑scale PyTorch training.
Enable Azure Managed Identities to protect credentials in ML pipelines.