Azure Machine Learning Python SDK is correct. Elena should use the Azure Machine Learning Python SDK to submit her training script from her local Python environment and have the run and metrics recorded in Azure Machine Learning.

The Azure Machine Learning Python SDK provides a programmatic Python API to create experiments or jobs configure compute targets upload datasets submit training runs and stream logs back to the Azure Machine Learning workspace. The SDK integrates with the workspace so Elena can launch training from her preferred IDE while still using the Azure Machine Learning tracking, model registry and compute resources.

Azure HDInsight is not correct because it is a managed Hadoop and Spark service for big data processing and not the Python API used to submit and track Azure Machine Learning experiments.

Azure CLI is not correct for this scenario because it is a command line tool for managing Azure resources and while it can perform some Azure Machine Learning tasks it is not the native Python library that a data scientist would use from their Python development environment to run and monitor experiments.

Azure Machine Learning studio is not correct because it refers to the web based studio and designer interfaces for building and monitoring experiments and not the Python package Elena would use to execute a training script from her local Python environment.

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