Google Cloud's pretrained model APIs use:

PDE - 6 Mixed Quiz

Quiz
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Science
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Professional Development
•
Medium
Supratim Bhattacharya
Used 2+ times
FREE Resource
7 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Your models and your data
Google's models and Google's data
Your models and Google's data
Google's models and your data
2.
MULTIPLE SELECT QUESTION
1 min • 1 pt
Which of the following are valid techniques for improving AutoML Vision and AutoML Natural Language models? (select two)
Increase the diversity and complexity of data
Increase the amount of training data
Increase the number of labels
Decrease the amount of training data
3.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Which statement best describes a data lake?
Storage optimized for high-throughput writes.
Data storage intended for analytics.
The place where you capture every aspect of your business operations. Data is stored in its natural, raw format.
Storage for current/historical data intended for reporting.
4.
MULTIPLE SELECT QUESTION
1 min • 1 pt
Which of the following statements are true? (Choose TWO)
Cloud SQL is optimized for high-throughput writes
Cloud SQL is optimized for high-read data
BigQuery is a row-based storage
BigQuery is optimized for high-read data
5.
MULTIPLE SELECT QUESTION
1 min • 1 pt
Which of the following statements are true? (Select all 2 correct responses)
Map operations in a MapReduce can be performed by Combine transforms in Dataflow
Dataflow transforms support both batch and streaming pipelines
Dataflow executes Apache Beam pipelines
Side-inputs in Dataflow are a way to export data from one pipeline to share with another pipeline
6.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Cloud Data Fusion is the ideal solution when you need
to build visual pipelines
Built only for batch data pipelines
a data warehousing solution
low-latency and high throughput processing of streaming data
7.
MULTIPLE SELECT QUESTION
1 min • 1 pt
Which of the following practices help optimize BigQuery queries?
Avoid using unnecessary columns
Filter early and often
Put the largest table on the left
Use COUNT(DISTINCT) instead of APPROX_COUNT_DISTINCT
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