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NEW QUESTION: 1
You plan to build a team data science environment. Data for training models in machine learning pipelines will be over 20 GB in size.
You have the following requirements:
Models must be built using Caffe2 or Chainer frameworks.

Data scientists must be able to use a data science environment to build the machine learning pipelines

and train models on their personal devices in both connected and disconnected network environments.
Personal devices must support updating machine learning pipelines when connected to a network.
You need to select a data science environment.
Which environment should you use?
A. Azure Databricks
B. Azure Machine Learning Studio
C. Azure Kubernetes Service (AKS)
D. Azure Machine Learning Service
Answer: D
Explanation:
Explanation/Reference:
Explanation:
The Data Science Virtual Machine (DSVM) is a customized VM image on Microsoft's Azure cloud built specifically for doing data science. Caffe2 and Chainer are supported by DSVM.
DSVM integrates with Azure Machine Learning.
Incorrect Answers:
B: Use Machine Learning Studio when you want to experiment with machine learning models quickly and easily, and the built-in machine learning algorithms are sufficient for your solutions.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/overview

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