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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare a model for deployment | 20-25% | - Manage deployment assets
|
| Topic 2: Explore data and train models | 35-40% | - Optimize model performance
|
| Topic 3: Design and prepare a machine learning solution | 20-25% | - Prepare development environments
|
| Topic 4: Deploy and retrain models | 10-15% | - Implement retraining pipelines
|
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NEW QUESTION # 435
You create an Azure Data Lake Storage Gen2 stowage account named storage1 containing a file system named fsi and a folder named folder1.
The contents of folder1 must be accessible from jobs on compute targets in the Azure Machine Learning workspace.
You need to construct a URl to reference folder1.
How should you construct the URI? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 436
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
An IT department creates the following Azure resource groups and resources:
The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks- cluster in the Azure Machine Learning workspace. You have a Microsoft Surface Book computer with a GPU.
Python 3.6 and Visual Studio Code are installed.
You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.
Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace. Run the training script as an experiment on the aks-cluster compute target.
Does the solution meet the goal?
Answer: A
Explanation:
Need to attach the mlvm virtual machine as a compute target in the Azure Machine Learning workspace.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-target
NEW QUESTION # 437
You create a binary classification model to predict whether a person has a disease.
You need to detect possible classification errors.
Which error type should you choose for each description? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://developers.google.com/machine-learning/crash-course/classification/true-false-positive-negative
NEW QUESTION # 438
You manage an Azure Machine Learning workspace. The Python script named seriptpy reads an argument named training_data. The training_data argument specifies the path to the training data in a file named datasetl.csv You plan to run the script.py Python script as a command job that trains a machine learning model.
You need to provide the command to pass the path for the dataset as a parameter value when you submit the script as a training job.
Solution: python script.py dataset1.csv
Does the solution meet the goal?
Answer: A
NEW QUESTION # 439
You manage an Azure Machine Learning workspace named workspace1 with a compute instance named compute1. You connect to compute! by using a terminal window from wofkspace1. You create a file named
"requirements.txt" containing Python dependencies to include Jupyler.
You need to add a new Jupyter kernel to compute1.
Which four commands should you use? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
NEW QUESTION # 440
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