AutoGluonΒΆ

AutoGluon-Tabular is a popular open-source AutoML framework that trains highly accurate machine learning models on an unprocessed tabular dataset. Unlike existing AutoML frameworks that primarily focus on model and hyperparameter selection, AutoGluon-Tabular succeeds by ensembling multiple models and stacking them in multiple layers.

The following table outlines a variety of sample notebooks that address different use cases of Amazon SageMaker AutoGluon-Tabular algorithm.

Notebook Title

Description

Tabular classification with Amazon SageMaker AutoGluon-Tabular algorithm

This notebook demonstrates the use of the Amazon SageMaker AutoGluon-Tabular algorithm to train and host a tabular classification model.

Tabular regression with Amazon SageMaker AutoGluon-Tabular algorithm

This notebook demonstrates the use of the Amazon SageMaker AutoGluon-Tabular algorithm to train and host a tabular regression model.

For instructions on how to create and access Jupyter notebook instances that you can use to run the example in SageMaker, see Use Amazon SageMaker Notebook Instances. After you have created a notebook instance and opened it, choose the SageMaker Examples tab to see a list of all of the SageMaker samples. To open a notebook, choose its Use tab and choose Create copy.

For detailed documentation, please refer to the Sagemaker AutoGluon-Tabular Algorithm.