Machine learning (ML) pipelines are used by data scientists to build, optimize, and manage their machine learning workflows. A typical pipeline involves a sequence of steps that cover the following areas:
The Azure Machine Learning SDK for Python can be used to create ML pipelines as well as to submit and track individual pipeline runs.
Module and ModuleVersion classes are added to manage reusable compute units in pipelines.
FAQs
Used to build, optimize, and manage their machine learning workflows.
We found that azureml-pipeline demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Popular npm packages like eslint-config-prettier were compromised after a phishing attack stole a maintainer’s token, spreading malicious updates.
Security News
/Research
A phishing attack targeted developers using a typosquatted npm domain (npnjs.com) to steal credentials via fake login pages - watch out for similar scams.
Security News
Knip hits 500 releases with v5.62.0, refining TypeScript config detection and updating plugins as monthly npm downloads approach 12M.
