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NEW QUESTION: 1
You have added two new tasks to your project. Both tasks are subtasks to a summary task. You need to update Baseline1 only for the two new tasks. What should you do?
A. Highlight the two tasks.Click Set Baseline and select Baseline1.Click the Selected Tasks radio button, and then click OK.
B. Highlight the two tasks.Click Set Baseline and select Baseline1.Click the Selected Tasks radio button, select To all summary tasks, and then click OK.
C. Highlight the summary task.Click Set Baseline and select Baseline1.Click the Selected Tasks radio button, select To all summary tasks, and then click OK.
D. Highlight the summary task.Click Set Baseline and select Baseline1.Click the Entire Project radio button, and then click OK.
Answer: B
NEW QUESTION: 2
John is traveling to a meeting that is 28 miles away. He needs to be there in 30 minutes. How fast does he need to go to make it to the meeting on time?
A. 49 mph
B. 25 mph
C. 41 mph
D. 56 mph
E. 37 mph
Answer: D
Explanation:
Explanation/Reference:
Explanation:
NEW QUESTION: 3
Under the same optical lens, the larger the imaging size, the smaller the field of view.
A. TRUE
B. FALSE
Answer: B
NEW QUESTION: 4
You create a multi-class image classification deep learning experiment by using the PyTorch framework. You plan to run the experiment on an Azure Compute cluster that has nodes with GPU's.
You need to define an Azure Machine Learning service pipeline to perform the monthly retraining of the image classification model. The pipeline must run with minimal cost and minimize the time required to train the model.
Which three pipeline steps should you run in sequence? 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
Step 1: Configure a DataTransferStep() to fetch new image data...
Step 2: Configure a PythonScriptStep() to run image_resize.y on the cpu-compute compute target.
Step 3: Configure the EstimatorStep() to run training script on the gpu_compute computer target.
The PyTorch estimator provides a simple way of launching a PyTorch training job on a compute target.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-pytorch