AutoGluon-Tabular - Amazon SageMaker
Amazon EC2 instance recommendation for the AutoGluon-Tabular algorithmSample Notebooks

AutoGluon-Tabular

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. This page includes information about Amazon EC2 instance recommendations and sample notebooks for AutoGluon-Tabular.

Amazon EC2 instance recommendation for the AutoGluon-Tabular algorithm

SageMaker AutoGluon-Tabular supports single-instance CPU and single-instance GPU training. Despite higher per-instance costs, GPUs train more quickly, making them more cost effective. To take advantage of GPU training, specify the instance type as one of the GPU instances (for example, P3). SageMaker AutoGluon-Tabular currently does not support multi-GPU training.

AutoGluon-Tabular sample notebooks

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 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.