Professional-Machine-Learning-Engineer Exam Question 1
You work for a manufacturing company. You need to train a custom image classification model to detect product defects at the end of an assembly line. Although your model is performing well, some images in your holdout set are consistently mislabeled with high confidence. You want to use Vertex AI to understand your model's results. What should you do?
Professional-Machine-Learning-Engineer Exam Question 2
You have been asked to productionize a proof-of-concept ML model built using Keras. The model was trained in a Jupyter notebook on a data scientist's local machine. The notebook contains a cell that performs data validation and a cell that performs model analysis. You need to orchestrate the steps contained in the notebook and automate the execution of these steps for weekly retraining. You expect much more training data in the future. You want your solution to take advantage of managed services while minimizing cost. What should you do?
Professional-Machine-Learning-Engineer Exam Question 3
You work for an organization that operates a streaming music service.
You have a custom production model that is serving a next song?recommendation based on a user's recent listening history.
Your model is deployed on a Vertex AI endpoint. You recently retrained the same model by using fresh data.
The model received positive test results offline. You now want to test the new model in production while minimizing complexity.
What should you do?
You have a custom production model that is serving a next song?recommendation based on a user's recent listening history.
Your model is deployed on a Vertex AI endpoint. You recently retrained the same model by using fresh data.
The model received positive test results offline. You now want to test the new model in production while minimizing complexity.
What should you do?
Professional-Machine-Learning-Engineer Exam Question 4
You work for a semiconductor manufacturing company. You need to create a real-time application that automates the quality control process. High-definition images of each semiconductor are taken at the end of the assembly line in real time. The photos are uploaded to a Cloud Storage bucket along with tabular data that includes each semiconductor's batch number, serial number, dimensions, and weight. You need to configure model training and serving while maximizing model accuracy. What should you do?
Professional-Machine-Learning-Engineer Exam Question 5
You are an AI engineer with an apparel retail company. The sales team has observed seasonal sales patterns over the past 5-6 years. The sales team analyzes and visualizes the weekly sales data stored in CSV files. You have been asked to estimate weekly sales for future seasons to optimize inventory and personnel workloads. You want to use the most efficient approach. What should you do?