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)
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
Latest DP-100 Dumps Valid Version with 227 Q&As
Latest And Valid Q&A | Instant Download | Once Fail, Full Refund