AutoGluon

6.8easy start · #5 of 36
in Predictive Analytics Software

Free to practise onyes
Free trialnot on record
Well documentedyes
Runs where you workyes

Runs on Linux, Mac, self-hosted, Windows.

AutoGluon is ranked #5 of 36 in predictive analytics software on The Geeks Club. It runs on Linux, macOS, Self-hosted, Windows. There is a free plan.

AutoGluon plans and pricing

All plans

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

Compared on predictive analytics software

Forecasting workflows: Yes
Model evaluation: Yes
Automated machine learning: Yes
Deployment mode: batch
Time-series modeling: Yes
API access: Yes

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The record

Purpose: AutoGluon automates machine learning for data such as tables and time series, helping users build predictive models with a few lines of code.
Tabular modeling: AutoGluon can train classification and regression models from tabular data while handling data cleaning, feature engineering, hyperparameter optimization, and model selection.
Time series: Its TimeSeriesPredictor trains multiple models to generate probabilistic forecasts for multiple time series using historical data and related covariates.
Multimodal: AutoMM reduces manual work in preprocessing, model selection, and fine-tuning to adapt foundation models to domain-specific data.
Supported tasks: The documentation includes image and text prediction, object detection, image segmentation, document prediction, entity extraction, and semantic matching examples.
Integrations: AutoMM adapts models from Hugging Face, TIMM, and MMDetection model zoos.
Forecasting models: Time-series forecasting combines methods including ETS and ARIMA from StatsForecast, LightGBM, DeepAR and Temporal Fusion Transformer from GluonTS, and Chronos.
Install requirements: AutoGluon requires Python 3.10 through 3.13 and supports Linux, macOS, and Windows.
GPU limitation: GPU usage is not supported on macOS; the installation guide directs users to Linux or Windows for GPU use.
SageMaker: AutoGluon is pre-installed in all releases of Amazon SageMaker Distribution.
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.
Cloud cost: AutoGluon-Cloud is described as a free wrapper, while SageMaker compute and S3 storage are billed to the user's AWS account.
Support: The project welcomes bug reports and feature requests through its GitHub issue tracker.
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.
Price from: Free

Where it ranks on The Geeks Club

Best Predictive Analytics Software in 2026#5 of 36
Best AutoML Software in 2026#8 of 28

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Sources

github.com/autogluon/autogluon· checked 3 Oct 2026
auto.gluon.ai/stable/tutorials/tabular/index.html· checked 3 Oct 2026
auto.gluon.ai/stable/tutorials/timeseries/index.html· checked 3 Oct 2026
auto.gluon.ai/stable/tutorials/multimodal/index.html· checked 3 Oct 2026
auto.gluon.ai/stable/index.html· checked 3 Oct 2026
auto.gluon.ai/stable/install.html· checked 3 Oct 2026
auto.gluon.ai/cloud/dev/tutorials/autogluon-cloud.htm· checked 3 Oct 2026
github.com/autogluon/autogluon/blob/master/CONTRIB· checked 3 Oct 2026
auto.gluon.ai· checked 28 Sept 2026