Correct Answers: A and D
AI Builder provides prebuilt and custom models in three categories: Text, Prediction, and Vision.
You can train the following model types: Text category: Category classification and Entity extraction
Prediction category: Prediction
Vision category: Form Processing, Object Detection
Three of these types don’t have prebuilt models: Prediction, Form Processing, Object Detection.
Before you train a model, you need to prepare the data. AI Builder is using the Dataverse database to store the training and model data. Some model types have their unique requirements for creating a model, like Form Processing model needs at least 5 form documents for training and Object Detection at least 15 pictures per object.
Option A is correct because you need to create a custom Dataverse table to store data for a Prediction model before training the model. You can import data into a custom table in Dataverse using the correct format.
Option D is correct because you can have not more than two times the images for one object in the training set to train the two objects detection model. You always need to make sure that your data is balanced.
Option B is incorrect because Microsoft recommends at least 5 form documents to train the Form Processing model.
Option C is incorrect because the training data must be in a Dataverse table in the correct format before training the custom Category classification model.
For more information about data preparation for custom AI builder models, please visit the below URLs:
https://docs.microsoft.com/en-us/ai-builder/prediction-data-prep
https://docs.microsoft.com/en-us/ai-builder/collect-images
https://docs.microsoft.com/en-us/ai-builder/form-processing-model-overview
https://docs.microsoft.com/en-us/ai-builder/before-you-build-text-classification-model
https://docs.microsoft.com/en-us/ai-builder/model-types