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DP-100: Azure Data Scientist Associate Exam Guide

Q: Which Azure ML tool offers a drag-and-drop interface for building ML pipelines?

Azure Machine Learning Designer.. Allows modeling and deployment without writing intensive code.

Q: How do you store a model for later deployment?

By using the Model Registry.. Manages model versioning, metadata, and handles the deployment lifecycle.

Q: Which component tracks model performance after deployment?

Model Monitoring.. Alerts when data drift or performance degradation occurs in production.

The **DP-100** certification is for Data Scientists who use Azure Machine Learning to train, evaluate, and deploy ML models.

What is the purpose of an Azure ML 'Compute Cluster'?

Respuesta : To provide scalable compute power for training and evaluating models.

Can auto-scale to zero nodes when idle to minimize costs.

Which Azure ML tool offers a drag-and-drop interface for building ML pipelines?

Respuesta : Azure Machine Learning Designer.

Allows modeling and deployment without writing intensive code.

What is 'AutoML'?

Respuesta : A feature that automatically tests multiple algorithms and parameters to find the best model.

Accelerates the data science process by choosing the optimal model architecture.

How do you store a model for later deployment?

Respuesta : By using the Model Registry.

Manages model versioning, metadata, and handles the deployment lifecycle.

Which component tracks model performance after deployment?

Respuesta : Model Monitoring.

Alerts when data drift or performance degradation occurs in production.