What is the general purpose of the AutoML category in Google Cloud's AI/ML portfolio?

To provide pre-trained models for common tasks like image recognition and translation

To manage the deployment and scaling of ML models in production

To give data scientists full control over every aspect of model architecture and training

To enable users with limited ML expertise to train custom models on their own data

Which of the following correctly lists the three main categories of Google Cloud AI/ML solutions?

Data preparation, model training, and model deployment

BigQuery ML, TensorFlow, and Vertex AI

Pre-trained APIs, AutoML, and custom model building

Vision, Natural Language, and Translation APIs

A large e-commerce company wants to build a product recommendation system. They have a team of ML engineers and a large dataset of user behavior. They need a model that can be updated frequently with new data and require low latency at inference. Which Google Cloud solution is most appropriate?

Vertex AI custom training with online prediction

Google CloudCloud Digital Leader

Domain 3Objective 2

Google Cloud’s AI and ML Solutions CLOUD-DIGITAL-LEADER Practice Questions (Page 1)

Part of the Innovating with Google Cloud Artificial Intelligence domain, which accounts for ~16% of the CLOUD-DIGITAL-LEADER exam.

28questions here

6free pages

7concepts

~16%of the exam

Questions 1–5

1foundation · easy
What is the general purpose of the AutoML category in Google Cloud's AI/ML portfolio?
Select an answer first
2foundation · easy
Which of the following correctly lists the three main categories of Google Cloud AI/ML solutions?
Select an answer first
3foundation · easy
A retail company wants to automatically detect defective products on an assembly line using images. They have a large dataset of labeled images of their products, but no ML engineers. Which Google Cloud solution should they use?
Select an answer first
4expert · hard
A large e-commerce company wants to build a product recommendation system. They have a team of ML engineers and a large dataset of user behavior. They need a model that can be updated frequently with new data and require low latency at inference. Which Google Cloud solution is most appropriate?
Select an answer first
5foundation · easy
A company has a large dataset of labeled images of their unique products and wants to train a model to recognize them, but they have no ML engineers on staff. Which Google Cloud solution is most appropriate?
Select an answer first

Finished these 5 questions?

Review the revealed explanations, or continue through the curriculum.

Next 5 questions →Back to CLOUD-DIGITAL-LEADER

Free Basic Practice is a study aid with revealable answers — not a scored exam. Examers.io is independent and not affiliated with or endorsed by Google Cloud. “CLOUD-DIGITAL-LEADER” is a trademark of its owner, used for identification only.

Google Cloud’s AI and ML Solutions CLOUD-DIGITAL-LEADER Practice Questions (Page 1)

Questions 1–5

What is the general purpose of the AutoML category in Google Cloud's AI/ML portfolio?

Which of the following correctly lists the three main categories of Google Cloud AI/ML solutions?

A retail company wants to automatically detect defective products on an assembly line using images. They have a large dataset of labeled images of their products, but no ML engineers. Which Google Cloud solution should they use?

A large e-commerce company wants to build a product recommendation system. They have a team of ML engineers and a large dataset of user behavior. They need a model that can be updated frequently with new data and require low latency at inference. Which Google Cloud solution is most appropriate?

A company has a large dataset of labeled images of their unique products and wants to train a model to recognize them, but they have no ML engineers on staff. Which Google Cloud solution is most appropriate?

Keep studying — Innovating with Google Cloud Artificial Intelligence