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AutoGluon

auto.gluon.ai

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Spec score 8.3 #6 of 37 in Predictive Analytics Software

What it is

AutoGluon is a free, open-source Python library for automating machine learning across tabular, time-series, and multimodal data. For tables, it trains classification and regression models while handling data cleaning, feature engineering, hyperparameter optimization, and model selection. Its TimeSeriesPredictor produces probabilistic forecasts for multiple time series using historical data and related covariates. AutoMM reduces manual work in adapting foundation models to specialized data. Documentation examples cover image and text prediction, object detection, image segmentation, document prediction, entity extraction, and semantic matching. AutoMM can adapt models from Hugging Face, TIMM, and MMDetection collections. Forecasting methods include ETS and ARIMA from StatsForecast, LightGBM, DeepAR and Temporal Fusion Transformer from GluonTS, and Chronos. AutoGluon supports Python 3.10 through 3.13 on Linux, macOS, and Windows. GPU usage is not supported on macOS; the installation guide points GPU users to Linux or Windows. AutoGluon is licensed under Apache 2.0. Cloud options include AutoGluon Cloud, described as a free wrapper, and Amazon SageMaker, where compute and S3 storage are billed to the user’s AWS account.

Spec sheet

Purpose
AutoGluon automates machine learning for data such as tables and time series, helping users build predictive models with a few lines of code.Read 3 Oct 2026 · github.com
Deployment
The project points to AutoGluon Cloud and deep learning containers for cloud training and deployment, and describes SageMaker Autopilot as a managed AutoGluon experience.Read 3 Oct 2026 · github.com
Integrations
AutoMM adapts models from Hugging Face, TIMM, and MMDetection model zoos.Read 3 Oct 2026 · auto.gluon.ai
Support
The project welcomes bug reports and feature requests through its GitHub issue tracker.Read 3 Oct 2026 · github.com
License
The AutoGluon library is licensed under Apache 2.0.Read 3 Oct 2026 · github.com
Founded
2019Read 28 Sep 2026 · auto.gluon.ai
Cloud cost
AutoGluon-Cloud is described as a free wrapper, while SageMaker compute and S3 storage are billed to the user's AWS account.Read 3 Oct 2026 · auto.gluon.ai
Forecasting models
Time-series forecasting combines methods including ETS and ARIMA from StatsForecast, LightGBM, DeepAR and Temporal Fusion Transformer from GluonTS, and Chronos.Read 3 Oct 2026 · auto.gluon.ai
GPU limitation
GPU usage is not supported on macOS; the installation guide directs users to Linux or Windows for GPU use.Read 3 Oct 2026 · auto.gluon.ai
Install requirements
AutoGluon requires Python 3.10 through 3.13 and supports Linux, macOS, and Windows.Read 3 Oct 2026 · auto.gluon.ai
Multimodal
AutoMM reduces manual work in preprocessing, model selection, and fine-tuning to adapt foundation models to domain-specific data.Read 3 Oct 2026 · auto.gluon.ai
SageMaker
AutoGluon is pre-installed in all releases of Amazon SageMaker Distribution.Read 3 Oct 2026 · auto.gluon.ai
Security reporting
The contribution guide asks users to report potential security issues to AWS/Amazon Security through its vulnerability reporting page rather than filing a public GitHub issue.Read 3 Oct 2026 · github.com
Supported tasks
The documentation includes image and text prediction, object detection, image segmentation, document prediction, entity extraction, and semantic matching examples.Read 3 Oct 2026 · auto.gluon.ai
Tabular modeling
AutoGluon can train classification and regression models from tabular data while handling data cleaning, feature engineering, hyperparameter optimization, and model selection.Read 3 Oct 2026 · auto.gluon.ai
Time series
Its TimeSeriesPredictor trains multiple models to generate probabilistic forecasts for multiple time series using historical data and related covariates.Read 3 Oct 2026 · auto.gluon.ai

Plans and prices

AutoGluon Free Open-source Python library · Apache 2.0 license Read 3 Oct 2026 · github.com

Every AutoGluon plan and price →

Strong points and limits

Strong points

  • Automates cleaning, feature engineering, and model selection.
  • Builds probabilistic forecasts for multiple series.
  • Documentation covers a broad set of prediction tasks.
  • Supports Linux, macOS, and Windows.
  • Licensed under Apache 2.0.

Limits

  • GPU usage is not supported on macOS.
  • SageMaker compute and S3 storage are billed separately.

Who it suits

It suits Python users building predictive models from tables, time series, images, text, or other listed data types. GPU users need Linux or Windows rather than macOS.

Verdict

AutoGluon handles several machine-learning workflows in a free, open-source Python library, with operating-system and Python-version requirements to check first. Cloud use through SageMaker carries compute and storage charges to the user’s AWS account.

Where Specifiction places it

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