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Microsoft DP-100 Exam Syllabus Topics:

SectionObjectives
Topic 1: Train machine learning models- Tune hyperparameters and evaluate models
- Train models using Azure Machine Learning
Topic 2: Optimize and manage models- Track experiments and manage model lifecycle
- Improve model performance
Topic 3: Deploy and consume models- Monitor deployed models and endpoints
- Deploy models to endpoints
Topic 4: Explore and analyze data- Ingest and prepare data for modeling
- Perform exploratory data analysis
Topic 5: Design and prepare a machine learning solution- Plan and configure Azure Machine Learning workspace
- Manage compute and data assets
- Select appropriate Azure services for machine learning workloads

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Microsoft Designing and Implementing a Data Science Solution on Azure 認定 DP-100 試験問題 (Q120-Q125):

質問 # 120
You create a script for training a machine learning model in Azure Machine Learning service.
You create an estimator by running the following code:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

正解：

解説：

Explanation:
Box 1: Yes
Parameter source_directory is a local directory containing experiment configuration and code files needed for a training job.
Box 2: Yes
script_params is a dictionary of command-line arguments to pass to the training script specified in entry_script.
Box 3: No
Box 4: Yes
The conda_packages parameter is a list of strings representing conda packages to be added to the Python environment for the experiment.


質問 # 121
Drag and Drop Question
You train and register a model by using the Azure Machine Learning Python SDK v2 on a local workstation. Python 3.7 and Visual Studio Code are installed on the workstation.
When you try to deploy the model into production to a Kubernetes online endpoint, you experience an error in the scoring script that causes deployment to fail.
You need to debug the service on the local workstation before deploying the service to production.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

正解：

解説：


質問 # 122
You need to configure the Edit Metadata module so that the structure of the datasets match. Which configuration options should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：

Explanation


質問 # 123
You manage an Azure Machine Learning workspace.
You plan to train a natural language processing (NLP) text classification model in multiple languages by using Azure Machine Learning Python SDK v2.
You need to configure the language of the text classification job by using automated machine learning.
Which method of the TextClassificationJob class should you use?

正解：B

解説：
https://learn.microsoft.com/en-us/python/api/azure-ai-
ml/azure.ai.ml.automl.textclassificationjob?view=azure-python#azure-ai-ml-automl- textclassificationjob-set-training-parameters


質問 # 124
You manage an Azure Machine Learning workspace named workspace1 and a Data Science Virtual Machine (DSVM) named DSMV1.
You must an experiment in DSMV1 by using a Jupiter notebook and Python SDK v2 code. You must store metrics and artifacts in workspace 1 You start by creating Python SCK v2 code to import ail required packages.
You need to implement the Python SOK v2 code to store metrics and article in workspace1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them the correctly order.

正解：

解説：

1 - Retrieve the tracking URl of worspace1.
2 - SEt the MLflow traking URl.
3 - Set the URI parameter of the mlflow.projects run method.


質問 # 125
......

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