@YutongTie-5848 (For whatever reason the reply button doesn't work for me, that's why I posted it this way.)
Well, let's say it's an email classification. So you got a .csv file where you have the text of an e-mail in one column and its class in the other column. Example could be:
"Click here to win $1000.",spam
"Hey, how are you?",normal
"Hello, PFA pictures.",normal
This is just an example with the text of the e-mails being just one sentence but you can imagine e-mails can be longer (like a paragraph or even more). You obviously can't treat a paragraph of text (like here) the same way you would treat a classification with the text being just one word.
I saw the e-mail classification (and other similar ones) being done in Azure AI gallery (https://gallery.azure.ai/Experiment/Email-Classification-for-Automated-Support-Ticket-Generation-Step-1-of-2-Train-and-Evaluate-Models-3) but that's in the studio/designer, not AutoML.
My expected result is classification but I wanted to know if AutoML can do other common tasks where NLP is used (named-entity recognition, sentiment analysis etc.).
When I choose the featurization settings, I see that there is a "Text" option as a feature type but one word is probably also "Text". So I'm asking if AutoML processes long strings in a different way.
I know there is the API but I would like to create models specifically via AutoML (or designer but preferably AutoML) for now.