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Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.

AutoGluon-Tabular

By: Amazon Web Services Latest Version: 3.3

Product Overview

AutoGluon-Tabular can save time by automating time-consuming manual steps—handling missing data, manual feature transformations, data splitting, model selection, algorithm selection, hyperparameter selection and tuning, ensembling multiple models, and repeating the process when data changes. Unlike existing AutoML frameworks that primarily focus on model/hyperparameter selection, AutoGluon-Tabular succeeds by ensembling multiple models and stacking them in multiple layers.

Key Data

Version
By Amazon Web Services
Categories
Type Algorithm
Fulfillment Methods Amazon SageMaker

Usage Information

Fulfillment Methods

Amazon SageMaker

Support Information

AutoGluon-Tabular

Search for questions and open new issues to ask questions.

https://autogluon.mxnet.io/tutorials/tabular_prediction/index.html

AWS Infrastructure

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Refund Policy

This product is offered for free. If there are any questions, please contact us for further clarifications.

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