Skip to main content

Used to build, optimize, and manage their machine learning workflows.

Project description

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:

  • Data preparation, such as normalizations and transformations
  • Model training, such as hyper parameter tuning and validation
  • Model deployment and evaluation

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.

Project details

Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Built Distribution

azureml_pipeline-1.38.0-py3-none-any.whl (3.7 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page