If you're looking to submit automated ML runs on a remote compute and don't need do any ML locally, we recommend using the thin client, azureml-train-automl-client, package that is part of the azureml-sdk. Also installs common data science packages including pandas, numpy, and scikit-learn. Provides classes for building and running automated machine learning experiments. Pip install -upgrade azureml-accel-models ![]() Pip install -upgrade azureml-automl-coreĪccelerates deep neural networks on FPGAs with the Azure ML Hardware Accelerated Models Service. This package is used by azureml-train-automl-client and azureml-train-automl-runtime. Additional packageĬontains core automated machine learning classes for Azure Machine Learning. The following table outlines the packages ,their use-cases and command to install, update & version check. These include dependencies that aren't required for all use-cases, so they are not included in the default installation in order to avoid bloating the environment. The SDK contains many other optional packages that you can install. To learn more about how to configure your development environment for Azure Machine Learning service, see Configure your development environment. You can also show the SDK version in Python, but this version does not include the minor version. To see all packages in your environment: pip list Verify your SDK version: pip show azureml-core Upgrade a previous version: pip install -upgrade azureml-core We recommend that you always keep azureml-core updated to the latest version.
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