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Google Exam Professional-Machine-Learning-Engineer Topic 4 Question 67 Discussion

Actual exam question for Google's Google Professional Machine Learning Engineer exam
Question #: 67
Topic #: 4
[All Google Professional Machine Learning Engineer Questions]

You work for a company that manages a ticketing platform for a large chain of cinemas. Customers use a mobile app to search for movies they're interested in and purchase tickets in the app. Ticket purchase requests are sent to Pub/Sub and are processed with a Dataflow streaming pipeline configured to conduct the following steps:

1. Check for availability of the movie tickets at the selected cinema.

2. Assign the ticket price and accept payment.

3. Reserve the tickets at the selected cinema.

4. Send successful purchases to your database.

Each step in this process has low latency requirements (less than 50milliseconds). You have developed a logistic regression model with BigQuery ML that predicts whether offering a promo code for free popcorn increases the chance of a ticket purchase, and this prediction should be added to the ticket purchase process. You want to identify the simplest way to deploy this model to production while adding minimal latency. What should you do?

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Suggested Answer: A

Contribute your Thoughts:

Celestine
11 days ago
Ooh, Merlyn, that's a clever idea! Putting the model in the mobile app is a really elegant solution. It ticks all the boxes - low latency, simplicity, and it avoids any external dependencies. I'm starting to like that option the most.
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Merlyn
12 days ago
Haha, looks like we've cracked the case! I can't wait to see the look on the examiner's face when we all select option D. They'll be like, 'Wow, these candidates really know their stuff!'
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Halina
13 days ago
Yeah, the more I think about it, option D does seem like the way to go. Having the promo code prediction happen right in the app is just so clean and efficient. Plus, it'll give our users a really seamless experience. I'm sold!
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