Answer-first summary for fast verification
Answer: Yes
The solution meets the goal because: 1) The Azure ML SDK can be installed on the local Surface Book with Python 3.6, 2) Running the training script as an experiment on local compute is supported in Azure ML, 3) The Surface Book has a GPU which is suitable for DNN training, 4) Metrics (loss and accuracy) can be logged to the Azure ML workspace when running locally using the SDK's logging capabilities. The community discussion strongly supports this with 78% choosing 'Yes', and key comments note that local compute can be used for training and metric logging without requiring the computer to be attached as a managed compute target. While some raised concerns about RAM or CUDA toolkit, these are not specified as requirements, and the core capability exists.
Author: LeetQuiz Editorial Team
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An IT department creates the following resources:
rgws in the rg resource groupaks-cluster in the rg resource group, which is attached to the ws workspace as a compute target named aks-clusterYou are using a Microsoft Surface Book with a GPU, which has Python 3.6 and Visual Studio Code installed.
You must run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.
Proposed Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace and then run the training script as an experiment on the local compute.
Does the solution meet the goal?
A
Yes
B
No
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