Which model type can BigQuery ML build?
Why C is the answer
Classification and forecasting models
BigQuery ML can build classification, regression, forecasting and clustering models.
In detail
- BigQuery ML builds classification and forecasting models, among others.
- It also supports regression and clustering.
Use case
An illustrative scenario, not a real incident.
A team builds a sales forecast in BigQuery ML, and a classifier in the same dataset.
See it in different ways
flowchart TD
A{"Where does the team work?"} -->|"SQL in BigQuery"| B["BigQuery ML"]
A -->|"No code, managed training"| C["Agent Platform AutoML"]
A -->|"Common task, no training needed"| D["Pre-built APIs: Document AI, Vision, Translate"]stateDiagram-v2 [*] --> Task Task --> PrebuiltApi: a common task Task --> BigQueryMl: data in BigQuery, SQL team Task --> AutoML: custom model, no code Task --> CustomTraining: your own code
mindmap
root(("BigQuery ML"))
n1["Types"]
n2["Classification"]
n3["Regression"]
n4["Forecasting"]
n5["Clustering"]Key point: BigQuery ML builds common model types.
Why the other options are wrong
- A. Only models trained outside of BigQuery and imported later
- It trains in BigQuery.
- B. None, because BigQuery is used only for storing data
- It does more than store data.
- D. Only image generation models, using custom containers
- It is not limited to images.