Microsoft Azure AI Engineer Associate AI-102 Practice Question
You plan to train a custom document intelligence model by selecting the "Unlabeled" option in Azure AI Document Intelligence Studio. All training files will be stored in a single Azure Blob Storage container named training-data. To make sure the training operation succeeds, which requirement must this container satisfy before you start the training job?
Every file name in the container must correspond to a row in a pre-defined schema table.
The container must include a model_data.json manifest file that lists the relative path of every training document.
Each document must reside in a separate subfolder together with a JSON label file generated by Document Intelligence Studio.
The container must contain at least five documents that have the same layout.
When you choose the Unlabeled (formerly "template") training option, Azure AI Document Intelligence only needs sample documents that share a common layout. No label files or folder hierarchy is required, but the service enforces a minimum document count so that it can reliably infer the template. The container must therefore hold at least five sample documents of the same form type. Placing each document in its own folder, adding label JSON files, or including a model_data.json manifest are requirements for labeled training jobs, not for unlabeled ones. Filenames do not have to match any schema table.
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Microsoft Azure AI Engineer Associate AI-102
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