AutoML Natural Language uses machine learning to analyze the structure and meaning of documents. You train a custom machine learning model to classify documents, extract information, or understand the sentiment of authors.
A classification model analyzes a document and returns a list of content categories that apply to the text found in the document.
An entity extraction model inspects a document for known entities referenced in the document and labels those entities in the text.
A sentiment analysis model inspects a document and identifies the prevailing emotional opinion within it, especially to determine a writer's attitude as positive, negative, or neutral.
Basic classification, entity extraction, and sentiment analysis are available through the Cloud Natural Language API. AutoML Natural Language enables you to define custom classification categories, entities, and sentiment scores that are relevant to your application.