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AutoGluon
What it is
AutoGluon is a free, open-source Python library that automates machine learning for tabular data, time series and multimodal tasks. For tables, it trains classification and regression models while handling data cleaning, feature engineering, hyperparameter optimization and model selection. Its TimeSeriesPredictor creates probabilistic forecasts for multiple series using historical data and related covariates. AutoMM reduces manual work when adapting foundation models to domain-specific data. Documentation examples cover image and text prediction, object detection, image segmentation, document prediction, entity extraction and semantic matching. AutoGluon can adapt models from Hugging Face, TIMM and MMDetection collections. Forecasting methods include ETS, ARIMA, LightGBM, DeepAR, Temporal Fusion Transformer and Chronos. It requires Python 3.10 through 3.13 and supports Linux, macOS and Windows. GPU use is not supported on macOS; the installation guide directs GPU users to Linux or Windows. The Apache 2.0-licensed library is available for self-hosted use. Cloud options include AutoGluon Cloud and deep learning containers; SageMaker compute and S3 storage are billed to the user's AWS account.
For and against
For
- Automates cleaning, feature engineering and model selection.
- Builds probabilistic forecasts across multiple time series.
- Supports Linux, macOS and Windows.
- Licensed under Apache 2.0.
- Includes examples across image, text and document tasks.
Against
- Requires Python 3.10 through 3.13.
- GPU use is not supported on macOS.
- SageMaker compute and S3 storage are billed separately.
The verdict
AutoGluon covers automated modeling for tables, time series and multimodal tasks in a free Python library. Mac users who need GPU support must use Linux or Windows, and cloud usage can involve AWS compute and storage charges.
Who it suits
AutoGluon suits Python users building predictive models from tabular, time-series or multimodal data. It may also suit users seeking examples for tasks such as object detection, document prediction or semantic matching.
Plans and prices
AutoGluon
Open-source Python library · Apache 2.0 license
Read 3 Oct 2026 · github.com
On the record
- Cloud cost
- AutoGluon-Cloud is described as a free wrapper, while SageMaker compute and S3 storage are billed to the user's AWS account.auto.gluon.ai · read 3 Oct 2026
- 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.github.com · read 3 Oct 2026
- Forecasting models
- Time-series forecasting combines methods including ETS and ARIMA from StatsForecast, LightGBM, DeepAR and Temporal Fusion Transformer from GluonTS, and Chronos.auto.gluon.ai · read 3 Oct 2026
- GPU limitation
- GPU usage is not supported on macOS; the installation guide directs users to Linux or Windows for GPU use.auto.gluon.ai · read 3 Oct 2026
- Install requirements
- AutoGluon requires Python 3.10 through 3.13 and supports Linux, macOS, and Windows.auto.gluon.ai · read 3 Oct 2026
- Integrations
- AutoMM adapts models from Hugging Face, TIMM, and MMDetection model zoos.auto.gluon.ai · read 3 Oct 2026
- License
- The AutoGluon library is licensed under Apache 2.0.github.com · read 3 Oct 2026
- Multimodal
- AutoMM reduces manual work in preprocessing, model selection, and fine-tuning to adapt foundation models to domain-specific data.auto.gluon.ai · read 3 Oct 2026
- Purpose
- AutoGluon automates machine learning for data such as tables and time series, helping users build predictive models with a few lines of code.github.com · read 3 Oct 2026
- SageMaker
- AutoGluon is pre-installed in all releases of Amazon SageMaker Distribution.auto.gluon.ai · read 3 Oct 2026
- 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.github.com · read 3 Oct 2026
- Support
- The project welcomes bug reports and feature requests through its GitHub issue tracker.github.com · read 3 Oct 2026
- Supported tasks
- The documentation includes image and text prediction, object detection, image segmentation, document prediction, entity extraction, and semantic matching examples.auto.gluon.ai · read 3 Oct 2026
- Tabular modeling
- AutoGluon can train classification and regression models from tabular data while handling data cleaning, feature engineering, hyperparameter optimization, and model selection.auto.gluon.ai · read 3 Oct 2026
- Time series
- Its TimeSeriesPredictor trains multiple models to generate probabilistic forecasts for multiple time series using historical data and related covariates.auto.gluon.ai · read 3 Oct 2026
