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Google Professional Machine Learning Engineer Exam - Topic 3 Question 47 Discussion

Your organization wants to make its internal shuttle service route more efficient. The shuttles currently stop at all pick-up points across the city every 30 minutes between 7 am and 10 am. The development team has already built an application on Google Kubernetes Engine that requires users to confirm their presence and shuttle station one day in advance. What approach should you take?
A) 1. Build a tree-based regression model that predicts how many passengers will be picked up at each shuttle station. 2. Dispatch an appropriately sized shuttle and provide the map with the required stops based on the prediction.
B) 1. Build a tree-based classification model that predicts whether the shuttle should pick up passengers at each shuttle station. 2. Dispatch an available shuttle and provide the map with the required stops based on the prediction
C) 1. Define the optimal route as the shortest route that passes by all shuttle stations with confirmed attendance at the given time under capacity constraints. 2 Dispatch an appropriately sized shuttle and indicate the required stops on the map
D) 1. Build a reinforcement learning model with tree-based classification models that predict the presence of passengers at shuttle stops as agents and a reward function around a distance-based metric 2. Dispatch an appropriately sized shuttle and provide the map with the required stops based on the simulated outcome.

Google Professional Machine Learning Engineer Exam - Topic 3 Question 47 Discussion

Actual exam question for Google's Professional Machine Learning Engineer exam
Question #: 47
Topic #: 3
[All Professional Machine Learning Engineer Questions]

Your organization wants to make its internal shuttle service route more efficient. The shuttles currently stop at all pick-up points across the city every 30 minutes between 7 am and 10 am. The development team has already built an application on Google Kubernetes Engine that requires users to confirm their presence and shuttle station one day in advance. What approach should you take?

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Suggested Answer: A

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Sheron
7 months ago
C is definitely the way to go for optimal routes!
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Shenika
7 months ago
I disagree, B is simpler and gets the job done.
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Melinda
7 months ago
Wait, a reinforcement learning model? That seems overkill!
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Bronwyn
8 months ago
I think A is better for predicting actual numbers.
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Cary
8 months ago
Option C sounds the most efficient!
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Felix
8 months ago
Option D sounds interesting with the reinforcement learning aspect, but it feels a bit complicated for this problem. I’m not sure if we need that level of sophistication.
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Cherry
8 months ago
I'm leaning towards option A because predicting the number of passengers seems crucial, but I wonder if a regression model is the best choice here.
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Francoise
8 months ago
I remember practicing a similar question where we had to decide between classification and regression models. I feel like option B might be too simplistic for this scenario, though.
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Thaddeus
8 months ago
I think option C makes the most sense since it focuses on the confirmed attendance and optimizing the route based on that. But I'm not entirely sure about the capacity constraints part.
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Genevieve
8 months ago
This question seems straightforward, but I want to make sure I understand the requirements correctly. I'll need to carefully review the details about the data storage and retention needs.
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Stevie
8 months ago
This seems like a straightforward question about sharing models. I think the key is understanding the requirement to have the sales engineers access the sales reps' accounts and opportunities.
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Lennie
8 months ago
Hmm, I'm a bit unsure about this one. I know CNAF policies can be used to protect against various attacks, but I'm not entirely clear on the specifics of how to configure it for XSS. I'll need to think this through carefully.
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