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| Section | Objectives |
|---|---|
| Topic 1: Explore and analyze data | - Perform exploratory data analysis - Ingest and prepare data for modeling |
| Topic 2: Optimize and manage models | - Track experiments and manage model lifecycle - Improve model performance |
| Topic 3: Train machine learning models | - Tune hyperparameters and evaluate models - Train models using Azure Machine Learning |
| Topic 4: Design and prepare a machine learning solution | - Manage compute and data assets - Plan and configure Azure Machine Learning workspace - Select appropriate Azure services for machine learning workloads |
| Topic 5: Deploy and consume models | - Monitor deployed models and endpoints - Deploy models to endpoints |
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NEW QUESTION # 440
You plan to implement a two-step pipeline by using the Azure Machine Learning SDK for Python.
The pipeline will pass temporary data from the first step to the second step.
You need to identify the class and the corresponding method that should be used in the second step to access temporary data generated by the first step in the pipeline.
Which class and method should you identify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point
Answer:
Explanation:
NEW QUESTION # 441
You manage an Azure Al Foundry project.
You develop a Prompt flow that includes a large language model (LLM) node and an upstream node with a single output. You need to link the LLM node input with the output of the upstream node by using a YAML flow configuration. Which flow configuration should you use?
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