Google Professional Machine Learning Engineer Question 67
Single answerGoogle Cloud PlatformYou are working for a retail company that wants to predict future sales based on historical data. The team has limited machine learning expertise, but they need an accurate model delivered quickly. Which Google Cloud tool would be most appropriate for developing the model in this scenario?
- A
AutoML Tables
- B
TensorFlow
- C
Pre-trained models in Vertex AI
- D
BigQuery ML
Show answer and explanation
Correct answer: A
Explanation
AutoML Tables is the best choice for this scenario because it is designed to handle tabular data and automates much of the model creation process, making it accessible to teams with limited machine learning expertise. It allows users to focus on their data rather than the technicalities of model building, ensuring a faster and more accurate delivery of results.
- A. Correct.
AutoML Tables is specifically designed for tabular data like sales data and is ideal for teams with limited machine learning expertise. It automates much of the model development process while still delivering accurate results.
- B. Incorrect.
TensorFlow is a powerful open-source machine learning framework, but it requires significant expertise to build and train models, which is not suitable for a team with limited ML knowledge.
- C. Incorrect.
Pre-trained models in Vertex AI are great for tasks like image recognition or natural language processing but are not meant for creating custom models based on tabular data like sales data.
- D. Incorrect.
BigQuery ML allows you to train models directly within BigQuery using SQL. While it can handle tabular data, it is less automated and typically requires more ML knowledge compared to AutoML Tables.