Microsoft
DP-100 · Question #169
Drag and Drop Question 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
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Drag and Drop Question 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:
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Configure a DataTransferStep() to fetch new image data from public web portal, running on the cpu-compute compute target.Configure an EstimatorStep() to run an estimator that runs the bird_classifier_train.py model training script on the gpu_compute compute target.Configure a PythonScriptStep() to run both image_fetcher.py and image_resize.py on the cpu-compute compute target.Configure an EstimatorStep() to run an estimator that runs the bird_classifier_train.py model training script on the gpu_compute compute target.Configure a PythonScriptStep() to run image_fetcher.py on the cpu-compute compute target.Configure a PythonScriptStep() to run image_resize.py on the cpu-compute compute target.Configure a PythonScriptStep() to run bird_classifier_train.py on the cpu-compute compute target.Configure a PythonScriptStep() to run bird_classifier_train.py on the cpu-compute compute target.
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Topics
#Azure ML Pipelines#MLOps#Deep Learning#Resource Optimization