What type of data can be used for training in Vertex AI?

The choice indicating that data from Google Cloud Storage or BigQuery can be used for training in Vertex AI is accurate because Vertex AI is designed to integrate seamlessly with Google Cloud's data storage solutions. This flexibility allows users to train machine learning models on diverse types of datasets, which can include structured data, unstructured data, images, and textual information.

Using data from Google Cloud Storage or BigQuery grants users access to vast amounts of data, catering to various machine learning needs and scenarios. For instance, structured data in BigQuery is suitable for tabular models, while unstructured data such as images and text can be easily stored in Google Cloud Storage and utilized for various model types. This versatility enhances the effectiveness of machine learning applications, enabling users to leverage their existing data infrastructure for model training and deployment.

In contrast, the other options each impose unnecessary constraints. The first choice, which suggests that only structured data can be used, is too limiting since Vertex AI can handle multiple data formats. The third option, referring exclusively to text-based data, overlooks the capabilities to train models using other forms of data, like images. Lastly, the option mentioning images only also disregards the wide range of data types that Vertex AI supports, including text and structured datasets. Therefore