Which environment should you use?

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 Machine Learning Service
B. Azure Machine Learning Studio
C. Azure Databricks
D. Azure Kubernetes Service (AKS)

View Answer

Answer: A

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.

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/overview