Azure Machine Learning Parallel Run Step
Project description
# Note This package has been deprecated and moved to [azureml-pipeline-steps](https://pypi.org/project/azureml-pipeline-steps/). Please refer to this [documentation](https://docs.microsoft.com/python/api/azureml-pipeline-steps) for more information.
# Azure Machine Learning Batch Inference
Azure Machine Learning Batch Inference targets large inference jobs that are not time-sensitive. Batch Inference provides cost-effective inference compute scaling, with unparalleled throughput for asynchronous applications. It is optimized for high-throughput, fire-and-forget inference over large collections of data.
# Getting Started with Batch Inference Public Preview
Batch inference public preview offers a platform in which to do large inference or generic parallel map-style operations. Please visit [Azure Machine Learning Notebooks](https://github.com/Azure/MachineLearningNotebooks) to find tutorials on how to leverage this service.
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.
Source Distributions
Built Distribution
Hashes for azureml_contrib_pipeline_steps-1.22.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 22314dcc4f80705b471ddc9a429f1dd8312233c9cea6cb08f33c561243ebab17 |
|
MD5 | 80d3b65751eccb9da79ec6dea06c1bb5 |
|
BLAKE2b-256 | 527765d3aba3790b732881e456b8c750c54a6ffdda46910979403e2cb4ff5e6f |