Welcome to ExamTopics
ExamTopics Logo
- Expert Verified, Online, Free.
exam questions

Exam Professional Machine Learning Engineer All Questions

View all questions & answers for the Professional Machine Learning Engineer exam

Exam Professional Machine Learning Engineer topic 1 question 200 discussion

Actual exam question from Google's Professional Machine Learning Engineer
Question #: 200
Topic #: 1
[All Professional Machine Learning Engineer Questions]

You work for a hotel and have a dataset that contains customers’ written comments scanned from paper-based customer feedback forms, which are stored as PDF files. Every form has the same layout. You need to quickly predict an overall satisfaction score from the customer comments on each form. How should you accomplish this task?

  • A. Use the Vision API to parse the text from each PDF file. Use the Natural Language API analyzeSentiment feature to infer overall satisfaction scores.
  • B. Use the Vision API to parse the text from each PDF file. Use the Natural Language API analyzeEntitySentiment feature to infer overall satisfaction scores.
  • C. Uptrain a Document AI custom extractor to parse the text in the comments section of each PDF file. Use the Natural Language API analyzeSentiment feature to infer overall satisfaction scores.
  • D. Uptrain a Document AI custom extractor to parse the text in the comments section of each PDF file. Use the Natural Language API analyzeEntitySentiment feature to infer overall satisfaction scores.
Show Suggested Answer Hide Answer
Suggested Answer: C 🗳️

Comments

Chosen Answer:
This is a voting comment (?) , you can switch to a simple comment.
Switch to a voting comment New
Foxy2021
1 month, 2 weeks ago
My vote is a. It is simple and do the job.
upvoted 1 times
...
AzureDP900
5 months ago
C is right Document AI custom extractor: Allows you to train a custom model to extract relevant information (in this case, customer comments) from the PDF files. Natural Language API analyzeSentiment feature: Analyzes the sentiment of the extracted text to predict an overall satisfaction score.
upvoted 1 times
...
bobjr
5 months, 3 weeks ago
Selected Answer: A
C & D are overkill We don't care about entities sentiment -> B is out Left with A and https://cloud.google.com/natural-language/docs/reference/rest/v1/documents/analyzeSentiment
upvoted 1 times
...
fitri001
7 months, 1 week ago
Selected Answer: C
Document AI custom extractor: Since the layout of the feedback forms is consistent, training a custom extractor in Document AI allows for efficient and accurate extraction of the specific comments section. This ensures the Natural Language API receives the relevant text for sentiment analysis. Natural Language API - analyzeSentiment: This functionality within the Natural Language API is specifically designed to analyze sentiment in a piece of text. It provides an overall sentiment score that can be mapped to a satisfaction score (e.g., high positive sentiment translates to high satisfaction).
upvoted 4 times
fitri001
7 months, 1 week ago
A. Vision API - parseText: While the Vision API can extract text from PDFs, it wouldn't necessarily target the specific comments section without a custom parser. B. Natural Language API - analyzeEntitySentiment: This feature focuses on sentiment analysis for named entities within the text. It might not be ideal for overall satisfaction extraction from general customer comments.
upvoted 1 times
...
...
pinimichele01
7 months, 2 weeks ago
Selected Answer: A
quickly predict an overall satisfaction -> a
upvoted 1 times
pinimichele01
7 months ago
no sorrt, it's C, you need doc AI
upvoted 1 times
...
...
edoo
8 months, 3 weeks ago
Selected Answer: A
I go with A, because "you need quickly predict", no time for fine-tunning.
upvoted 2 times
...
guilhermebutzke
9 months, 2 weeks ago
Selected Answer: C
My answer: Letter C Document AI is a suitable tool for cases where there are patterns of forms or documentation. Additionally, it is possible to directly read PDF files. In the Natural Language API, the analyzeSentiment function can determine the overall sentiment, as the text asks, "You need to quickly predict an overall satisfaction." The analyzeEntitySentiment function provides a score for each entity or word found. https://cloud.google.com/natural-language/docs/basics
upvoted 1 times
...
ddogg
9 months, 3 weeks ago
Selected Answer: C
Document AI custom extractor: This allows you to tailor the text extraction specifically to the layout and format of your customer feedback forms, ensuring accurate capture of the comments section. Natural Language API analyzeSentiment: This feature analyzes the extracted text and provides an overall sentiment score, which can be used to gauge customer satisfaction.
upvoted 1 times
...
pikachu007
10 months, 2 weeks ago
Selected Answer: C
Precision in text extraction: Document AI is specifically designed for extracting text from structured documents like forms, ensuring accurate extraction of comments, even with varying handwriting styles. Custom model for form layout: Training a custom extractor tailored to the hotel's feedback form layout further enhances accuracy and targets the relevant comments section effectively. Sentiment analysis: Natural Language API's analyzeSentiment feature analyzes overall sentiment in a text block, aligning with the goal of deriving overall satisfaction scores.
upvoted 1 times
...
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.

SaveCancel
Loading ...