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NEW QUESTION: 1
SKI : SNOW
A. drive: car
B. ride: horse
C. skate: ice
D. gold: putt
E. dance: step
Answer: C
NEW QUESTION: 2
A donor donates $500 to a nonprofit that is matched by his employer. How are the hard credits and soft credits listed in NPSP?
A. The donor has a hard credit of $500 and a soft credit of $500, and the employer has a hard credit of $500
B. The donor has a hard credit of $500, the employer has a hard credit of $500, and there are no soft credits
C. The donor has a hard credit of $500 and the employer has a soft credit of $500
D. The donor has a soft credit of $500 and the employer has a hard credit of $500
Answer: D
NEW QUESTION: 3
Which SAN topologies offer the highest centralized data access performance? {Select two.)
A. single switch
B. ring
C. cascaded
D. meshed
E. core-edge
Answer: C,E
NEW QUESTION: 4
HOTSPOT
You are designing an Azure infrastructure to support an Azure Machine Learning solution that will have multiple phases. The solution must meet the following requirements:
* Securely query an on-premises database once a week to update product lists.
* Access the data without using a gateway.
* Orchestrate the separate phases.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Azure App Service Hybrid Connections
With Hybrid Connections, Azure websites and mobile services can access on-premises resources as if they were located on the same private network. Application admins thus have the flexibility to simply lift-and-shift specific most front-end tiers to Azure with minimal configuration changes, extending their enterprise apps for hybrid scenarios.
IncorrectAnswer: The VPN connection solution both use gateways.
Box 2: Machine Learning pipelines
Typically when running machine learning algorithms, it involves a sequence of tasks including pre- processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and cleaning, extracting features, and training a classification model with cross-validation. Though there are many libraries we can use for each stage, connecting the dots is not as easy as it may look, especially with large-scale datasets. Most ML libraries are not designed for distributed computation or they do not provide native support for pipeline creation and tuning.
Box 3: Azure Databricks
References:
https://azure.microsoft.com/is-is/blog/hybrid-connections-preview/
https://databricks.com/glossary/what-are-ml-pipelines