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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design and prepare a machine learning solution | 20-25% | - Prepare development environments
|
| Topic 2: Deploy and retrain models | 10-15% | - Monitor deployed models
|
| Topic 3: Explore data and train models | 35-40% | - Optimize model performance
|
| Topic 4: Prepare a model for deployment | 20-25% | - Deploy machine learning models
|
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NEW QUESTION # 300
You are planning to register a trained model in an Azure Machine Learning workspace.
You must store additional metadata about the model in a key-value format. You must be able to add new metadata and modify or delete metadata after creation.
You need to register the model.
Which parameter should you use?
Answer: A
Explanation:
Explanation
azureml.core.Model.properties:
Dictionary of key value properties for the Model. These properties cannot be changed after registration, however new key value pairs can be added.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.model.model
NEW QUESTION # 301
You are using hyperparameter tuning in Azure Machine Learning Python SDK v2 to train a model. You configure the hyperparameter tuning experiment by running the following code:
For each of the following statements select Yes if the statement is true. Otherwise, select No. NOTE: Fach correct selection is worth one paint.
Answer:
Explanation:
NEW QUESTION # 302
Hotspot Question
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.
Answer:
Explanation:
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.
NEW QUESTION # 303
You are implementing a machine learning model to predict stock prices.
The model uses a PostgreSQL database and requires GPU processing.
You need to create a virtual machine that is pre-configured with the required tools.
What should you do?
Answer: B
Explanation:
In the DSVM, your training models can use deep learning algorithms on hardware that's based on graphics processing units (GPUs).
PostgreSQL is available for the following operating systems: Linux (all recent distributions), 64-bit installers available for macOS (OS X) version 10.6 and newer - Windows (with installers available for 64-bit version; tested on latest versions and back to Windows 2012 R2.
Incorrect Answers:
B: The Azure Geo AI Data Science VM (Geo-DSVM) delivers geospatial analytics capabilities from Microsoft's Data Science VM. Specifically, this VM extends the AI and data science toolkits in the Data Science VM by adding ESRI's market-leading ArcGIS Pro Geographic Information System.
C, D: DLVM is a template on top of DSVM image. In terms of the packages, GPU drivers etc are all there in the DSVM image. Mostly it is for convenience during creation where we only allow DLVM to be created on GPU VM instances on Azure.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/overview
NEW QUESTION # 304 
You need to record the row count as a metric named row_count that can be returned using the get_metrics method of the Run object after the experiment run completes. Which code should you use?
Answer: C
Explanation:
Log a numerical or string value to the run with the given name using log(name, value, description=''). Logging a metric to a run causes that metric to be stored in the run record in the experiment. You can log the same metric multiple times within a run, the result being considered a vector of that metric.
Example: run.log("accuracy", 0.95)
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.run
NEW QUESTION # 305
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