Google Professional Machine Learning Engineer Question 69
Single answerGoogle Cloud PlatformYou are a Machine Learning Engineer tasked with building a custom image classification model to classify product images for an e-commerce platform. Your team lacks deep expertise in machine learning but needs a solution that provides a balance between ease of use and performance. Which Google Cloud product would best meet your needs?
- A
AutoML Vision
- B
Vertex AI Custom Training
- C
BigQuery ML
- D
TensorFlow on Google Cloud
Show answer and explanation
Correct answer: A
Explanation
AutoML Vision is specifically built for users who may not have in-depth knowledge of machine learning and need an accessible solution for creating custom models. It abstracts much of the complexity of model building and provides an intuitive interface, making it the ideal choice for the scenario described.
- A. Correct.
AutoML Vision is designed for users with limited machine learning expertise. It provides an easy-to-use interface to train high-performing custom image classification models without requiring deep knowledge of ML pipelines.
- B. Incorrect.
Vertex AI Custom Training is a powerful option for building custom models, but it requires significant expertise in machine learning and managing training pipelines. It may not be the best fit for a team with limited ML experience.
- C. Incorrect.
BigQuery ML is primarily designed for running machine learning models directly on structured data in BigQuery and does not focus on image classification tasks.
- D. Incorrect.
TensorFlow on Google Cloud offers flexibility for creating highly customized models, but it requires advanced ML knowledge and is not the most suitable choice for a team with limited expertise.