| title | titleSuffix | description | author | manager | ms.service | ms.topic | ms.date | ms.author | ms.custom | zone_pivot_groups |
|---|---|---|---|---|---|---|---|---|---|---|
Quickstart - Custom text classification |
Azure AI services |
Quickly start building an AI model to identify and apply labels (classify) unstructured text. |
jboback |
nitinme |
azure-ai-language |
quickstart |
12/19/2023 |
jboback |
language-service-custom-classification, mode-other |
usage-custom-language-features |
Use this article to get started with creating a custom text classification project where you can train custom models for text classification. A model is artificial intelligence software that's trained to do a certain task. For this system, the models classify text, and are trained by learning from tagged data.
Custom text classification supports two types of projects:
- Single label classification - you can assign a single class for each document in your dataset. For example, a movie script could only be classified as "Romance" or "Comedy".
- Multi label classification - you can assign multiple classes for each document in your dataset. For example, a movie script could be classified as "Comedy" or "Romance" and "Comedy".
In this quickstart you can use the sample datasets provided to build a multi label classification where you can classify movie scripts into one or more categories or you can use single label classification dataset where you can classify abstracts of scientific papers into one of the defined domains.
::: zone pivot="language-studio"
[!INCLUDE Language Studio quickstart]
::: zone-end
::: zone pivot="rest-api"
[!INCLUDE REST API quickstart]
::: zone-end
After you've created a custom text classification model, you can:
When you start to create your own custom text classification projects, use the how-to articles to learn more about developing your model in greater detail: