Below are five different types of AI models.

1. Form Processing
2. Object Detection
3. Entity Extraction
4. Category Classification
5. Prediction

1. Form Processing – This model extracts text from any matching form by identifying the structure of our documents based on examples we provide.

We have five data attributes to obtain from the passport in this example: Passport Number, Birth date, Date Of issue, Date Of expiry, and Birthplace. The image above depicts how we prepare the model to process forms.

Use case: Models can be trained to process invoices, passports, driver’s licence, and tax forms.

recommendation: Microsoft advises training with a minimum of five papers. However, it is preferable to train the model with more documents. I can tell that effectiveness is determined by the number of documents and the kind of documents we trained on, such as jpeg, pdf, and various formats.

2. Object Detection — This model aids in the detection and identification of certain items within any image. This model may be used in PowerApps to extract data from photos taken with the camera.

recommendation: Microsoft suggests 15 or more pictures per object, while 50 or more is preferable. In the same image, we can tag two items. Each image should be up to 6 MB in size and be in one of the following formats:.jpg,.png, or.bmp.

3. Entity Extraction — Depending on our business requirements, this model extracts relevant data from text. This model aids in the transformation of unstructured information into structured information.

Use case: The model can extract data from emails and save it as distinct metadata in Sharepoint, DataVerse, or any other application.

The maximum length of a document is 5,000 characters. English, Chinese-Simplified, French, German, Portuguese, Italian, and Spanish are all supported languages. We have a couple listings of entity kinds that are supported.

4. Classification by Category — This methodology divides the text into categories. It can be used with the canvas app or with Power Automate.

Use case: Sentiment analysis, spam detection, and customer request routing are examples of use cases.

Recommendations: Each tag must have at least 10 text entries.

5. Prediction – Based on the past data we provided, it makes predictions. This model forecasts future events.

Types:

1. There are two alternatives available. (binary)
2. From a variety of possible outcomes
3. When the response is a number.