4.1.1 AutoML Ease of Use

The AutoML feature of MySQL AI is purpose-built for ease of use. It requires no machine learning expertise, specialized tools, or algorithms. With AutoML and a set of training data, you can train a predictive machine learning model with a single call to the ML_TRAIN SQL routine.

For example:

CALL sys.ML_TRAIN('heatwaveml_bench.census_train', 'revenue', NULL, @census_model);

The ML_TRAIN routine leverages Oracle AutoML technology to automate training of machine learning models. Learn more about Oracle AutoML.

You can use a model created by ML_TRAIN with other AutoML routines to generate predictions and explanations. For example, the following call to the ML_PREDICT_TABLE routine generates predictions for a table of input data:

CALL sys.ML_PREDICT_TABLE('heatwaveml_bench.census_test', @census_model, 
'heatwaveml_bench.census_predictions', NULL);

All AutoML operations are initiated by running CALL or SELECT statements, which can be easily integrated into your applications. AutoML routines reside in the MySQL sys schema. Learn more about AutoML Routines.

In addition, with AutoML, there is no need to move or reformat your data, which saves you time and effort while keeping your data and models secure.

To start using AutoML with sample datasets, see Machine Learning Use Cases.

What's Next

• Learn more about the following:

  • AutoML Supervised Learning

  • AutoML Workflow

  • Oracle AutoML

• Learn how to Create a Machine Learning Model.