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Microsoft Azure Machine Learning Python client library
Microsoft Azure Synapse Spark Client Library for Python
Microsoft Azure Synapse Artifacts Client Library for Python
Microsoft Azure Synapse AccessControl Client Library for Python
Microsoft Azure Storage Namespace Package [Internal]
Contains the integration code of AzureML with Mlflow.
Microsoft Azure Machine Learning Python SDK for authoring web services
Used to build, optimize, and manage their machine learning workflows.
Contains core functionality for Azure Machine Learning pipelines, which are configurable machine learning workflows.
Machine Learning interpret package is used to interpret ML models
Core functionalities for data-type definition, data io and frequently-used functions.
Provide functionalities to invoke Azure Machine Learning designer built-in modules in deployment service.
Provides utilities for users which allows for handling of the raw http requests in webservices.
The package is to coordinate dependencies within AzureML packages. This package is internal, and is not intended to be used directly.
Is a metapackage that is used internally by Azure Machine Learning
Contains the ML and non-Azure specific common code associated with running AutoML for public use.
(v1) Manage Azure Machine Learning resources. It is recommended to use the 2.0 extension - see aka.ms/azml2
Contains the non-ML non-Azure specific common code associated with running AutoML.
Used for automatically finding the best machine learning model and its parameters.
Used for automatically finding the best machine learning model and its parameters.
Provides estimators for training models.
Used for automatically finding the best machine learning model and its parameters.
Used to build and run machine learning workflows upon the Azure Machine Learning service.
Used to collect telemetry data like Log messages, metrics, events, and activity messages
Aeva : represents a unit of computation in azureml-pipeline
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