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The DP-100 exam covers a wide range of topics, including data exploration and preparation, modeling, deployment, and monitoring. You will need to demonstrate your proficiency in using Azure services like Azure Machine Learning, Azure Databricks, Azure Stream Analytics, and Azure Cognitive Services to build end-to-end ML solutions.
Microsoft DP-100 is a certification exam that focuses on designing and implementing data science solutions on Azure. DP-100 Exam validates the candidate's knowledge and skills in using Azure technologies to build and deploy machine learning models, data pipelines, and data analysis solutions. The DP-100 certification is designed for data scientists, data engineers, and other professionals who work with data and want to demonstrate their expertise in Azure-based data science solutions.
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The DP-100 Exam covers a range of topics, including creating and managing data sets, building and training predictive models, deploying models to production environments, and monitoring and optimizing the performance of models. Candidates will be required to demonstrate their ability to work with Azure Machine Learning, Azure Databricks, and other Azure data services, and to use tools such as Python and R to design and implement data solutions.
NEW QUESTION # 476
You train a machine learning model by using Aunt Machine Learning.
You use the following training script m Python to log an accuracy value.
You must use a Python script to define a sweep job.
You need to provide the primary metric and goal you want hyper parameter tuning to optimize.
How should you complete the Python script? To answer select the appropriate options in the answer area NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 477
You create an Azure Machine Learning workspace. You use the Azure Machine Learning Python SDK v2 to create a compute cluster.
The compute cluster must run a training script. Costs associated with running the training script must be minimized.
You need to complete the Python script to create the compute cluster.
How should you complete the script? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 478
You deploy a model in Azure Container Instance.
You must use the Azure Machine Learning SDK to call the model API.
You need to invoke the deployed model using native SDK classes and methods.
How should you complete the command? To answer, select the appropriate options in the answer areas.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/how-to-deploy-azure-container-instance
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-deployment
NEW QUESTION # 479
You need to build a feature extraction strategy for the local models.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 480
You use an Azure Machine Learning workspace. Azure Data Factor/ pipeline, and a dataset monitor that runs en a schedule to detect data drift.
You need to Implement an automated workflow to trigger when the dataset monitor detects data drift and launch the Azure Data Factory pipeline to update the dataset. The solution must minimize the effort to configure the workflow.
How should you configure the workflow? To answer select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 481
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