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Google Professional Machine Learning Engineer Exam - Topic 6 Question 5 Discussion

You are designing an architecture with a serveress ML system to enrich customer support tickets with informative metadata before they are routed to a support agent. You need a set of models to predict ticket priority, predict ticket resolution time, and perform sentiment analysis to help agents make strategic decisions when they process support requests. Tickets are not expected to have any domain-specific terms or jargon.The proposed architecture has the following flow:Which endpoints should the Enrichment Cloud Functions call?
B) 1 = Al Platform, 2 = Al Platform, 3 = AutoML Natural Language
A) 1 = Al Platform, 2 = Al Platform, 3 = AutoML Vision
C) 1 = Al Platform, 2 = Al Platform, 3 = Cloud Natural Language API
D) 1 = cloud Natural Language API, 2 = Al Platform, 3 = Cloud Vision API

Google Professional Machine Learning Engineer Exam - Topic 6 Question 5 Discussion

Actual exam question for Google's Professional Machine Learning Engineer exam
Question #: 5
Topic #: 6
[All Professional Machine Learning Engineer Questions]

You are designing an architecture with a serveress ML system to enrich customer support tickets with informative metadata before they are routed to a support agent. You need a set of models to predict ticket priority, predict ticket resolution time, and perform sentiment analysis to help agents make strategic decisions when they process support requests. Tickets are not expected to have any domain-specific terms or jargon.

The proposed architecture has the following flow:

Which endpoints should the Enrichment Cloud Functions call?

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Suggested Answer: B

by Sharee at May 08, 2022, 01:51 PM

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Santos
10 months ago
Option D sounds interesting, but I'm not sure about using Cloud Vision here.
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Detra
10 months ago
I agree with B, it covers all the bases for ticket enrichment.
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Beckie
11 months ago
Wait, why would we use AutoML Vision for support tickets? That seems off.
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Willis
11 months ago
I think option C is better for the Natural Language tasks.
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Richelle
11 months ago
Definitely going with option B, makes the most sense for sentiment analysis!
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Belen
11 months ago
I have a hunch that option C is correct since it mentions the Cloud Natural Language API, which seems perfect for sentiment analysis.
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Amie
11 months ago
I'm not entirely sure, but I feel like the Cloud Natural Language API is specifically designed for text analysis, which could fit here.
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Theola
11 months ago
I remember we discussed using AutoML for natural language tasks, so I think option B might be right.
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Melodie
11 months ago
This question is tricky! I think we practiced something similar, but I can't recall if we used AutoML Vision for anything related to text.
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Merissa
11 months ago
Ah, I remember learning about this in class. If an attacker can find two values that hash to the same output, that's called a collision. It's a major security vulnerability that can be exploited, so I'll make sure to select that option.
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Jaime
11 months ago
I think moving static content deployment to the build phase could work, but I'm not completely sure if it would eliminate the downtime entirely.
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Rhea
11 months ago
I've used Arxscan before, and I know it's great for analyzing SAN performance, network performance, and storage capacity. Those are the three tasks I'll select.
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Taryn
11 months ago
I remember that MP-iBGP sessions need to be established between the PE routers, but I'm unsure if it's BB-PE-A and CC-PE-B or another pair.
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