Welcome to AutoML Natural Language, which enables you to create custom machine learning models to classify English-language content into a custom set of categories.
Custom machine learning models for classifying content are useful when the pre-defined categories that are available from the Natural Language API are too generic or not applicable to your specific use case or knowledge domain.
You can use the AutoML Natural Language UI to upload your training data, train, and test your custom model.
If you don't need a custom model solution, the Cloud Natural Language API provides content classification, entity and sentiment analysis, and more.
In this section
- Quickstart - Use the AutoML Natural Language UI to train and validate a custom model for classifying content.
- Before you begin - Information on setting up a Google Cloud Platform project that you can use with AutoML Natural Language. (This information is also in the Quickstart.)
- Preparing your training data - Information on preparing and formatting training data for AutoML Natural Language.
- Creating datasets, training models, and evaluating results - How to complete the main steps in creating your custom model.
- Classifying content - Using your custom model to classify content.
- REST Reference
- RPC Reference
You can view discussions and post questions and feedback to the Natural Language discussion group.