Question 1

You are an ML engineer on an agricultural research team working on a crop disease detection tool to detect leaf rust spots in images of crops to determine the presence of a disease. These spots, which can vary in shape and size, are correlated to the severity of the disease. You want to develop a solution that predicts the presence and severity of the disease with high accuracy. What should you do?

Options :

A : Create an object detection model that can localize the rust spots.

B : Develop an image segmentation ML model to locate the boundaries of the rust spots.

C : Develop a template matching algorithm using traditional computer vision libraries.

D : Develop an image classification ML model to predict the presence of the disease.

Answer: B

Question 2

You are an ML engineer at an ecommerce company and have been tasked with building a model that predicts how much inventory the logistics team should order each month. Which approach should you take?

Options :

A : Use a clustering algorithm to group popular items together. Give the list to the logistics team so they can increase inventory of the popular items.

B : Use a regression model to predict how much additional inventory should be purchased each month. Give the results to the logistics team at the beginning of the month so they can increase inventory by the amount predicted by the model.

C : Use a time series forecasting model to predict each item-s monthly sales. Give the results to the logistics team so they can base inventory on the amount predicted by the model.

D : Use a classification model to classify inventory levels as UNDER_STOCKED, OVER_STOCKED, and CORRECTLY_STOCKEGive the report to the logistics team each month so they can fine-tune inventory levels.

Answer: C

Question 3

You work for a delivery company. You need to design a system that stores and manages features such as parcels delivered and truck locations over time. The system must retrieve the features with low latency and feed those features into a model for online prediction. The data science team will retrieve historical data at a specific point in time for model training. You want to store the features with minimal effort. What should you do?

Options :

A : Store features in Bigtable as key/value data.

B : Store features in Vertex Al Feature Store.

C : Store features as a Vertex Al dataset and use those features to tram the models hosted in Vertex Al endpoints.

D : Store features in BigQuery timestamp partitioned tables, and use the BigQuery Storage Read API to serve the features.

Answer: B

Question 4

Your team is building an application for a global bank that will be used by millions of customers. You built a forecasting model that predicts customers' account balances 3 days in the future. Your team will use the results in a new feature that will notify users when their account balance is likely to drop below $25. How should you serve your predictions?

Options :

A : 1. Create a Pub/Sub topic for each user. 2. Deploy a Cloud Function that sends a notification when your model predicts that a user-s account balance will drop below the $25 threshold.

B : 1. Create a Pub/Sub topic for each user. 2. Deploy an application on the App Engine standard environment that sends a notification when your model predicts that a user-s account balance will drop below the $25 threshold.

C : 1. Build a notification system on Firebase. 2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when the average of all account balance predictions drops below the $25 threshold.

D : 1. Build a notification system on Firebase. 2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when your model predicts that a user-s account balance will drop below the $25 threshold.

Answer: D

Question 5

You work for a toy manufacturer that has been experiencing a large increase in demand. You need to build an ML model to reduce the amount of time spent by quality control inspectors checking for product defects. Faster defect detection is a priority. The factory does not have reliable Wi-Fi. Your company wants to implement the new ML model as soon as possible. Which model should you use?

Options :

A : AutoML Vision Edge mobile-high-accuracy-1 model

B : AutoML Vision Edge mobile-low-latency-1 model

C : AutoML Vision model

D : AutoML Vision Edge mobile-versatile-1 model

Answer: B

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