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NEW QUESTION: 1
PyTorchフレームワークを使用して、マルチクラス画像分類の深層学習実験を作成します。 GPUを備えたノードを持つAzure Computeクラスターで実験を実行する予定です。
画像分類モデルの毎月の再トレーニングを実行するには、Azure Machine Learningサービスパイプラインを定義する必要があります。パイプラインは最小限のコストで実行し、モデルのトレーニングに必要な時間を最小限に抑える必要があります。
どの3つのパイプラインステップを順番に実行する必要がありますか？回答するには、適切なアクションをアクションのリストから回答領域に移動し、正しい順序に並べます。

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

NEW QUESTION: 2
A customer has a single Visualforce page that allows each user to input up to 1500 sales forecasts and instantly view pivoted forecast calculations. Users are complaining that the page is loading slowly, and they are seeing error messages regarding heap and view state limits. What are three recommendations to optimize page performance?
A. Specify the list of sales forecasts as transient.
B. Use JavaScript Remoting instead of controller actions.
C. Create formula fields to compute pivoted forecast calculations.
D. Segregate calculation functionality from input functionality.
E. Implement pagination and reduce records per page.
Answer: B,C,E

NEW QUESTION: 3
The following basic principles for fault location in WDM systems are (). (Multiple Choice)
A. First advanced, then low level
B. First locate external and then location transmission
C. First two-way, then one-way first
D. First single wave, followed by multiple waves
Answer: A,B,C

NEW QUESTION: 4
What software is used to manage infrastructure on the XC Series?
A. Nutanix Prism
B. Nutanix CALM
C. Acropolis Distributed Storage Fabric
D. Quick Sync2
Answer: A