autogluon/autogluon

Health v2 · maintenance only

Adoption not part of the score

10617 stars · 1181 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

AutoGluon is an AutoML library that automates machine learning on tabular data, time series, text, and images with just a few lines of Python code. It automatically selects and ensembles models—from classic ML algorithms to deep learning foundation models—to achieve strong predictive performance.

Use cases

• train accurate models on tabular data with minimal code
• forecast time series automatically
• classify text and images without tuning hyperparameters
• build ensembles of ML models automatically
• quickly prototype predictive models on a CSV dataset
• automate model selection and hyperparameter optimization

When to choose

• you want strong predictive accuracy without ML expertise or manual tuning
• you need fast baselines on tabular, time series, text, or image data
• you want automated ensembling and hyperparameter search out of the box

When to avoid

• you need full control over individual model architectures and training pipelines
• you require minimal dependencies or very lightweight deployment
• you need real-time low-latency inference with strict resource constraints

Facets

library · maturity active

machine-learning deep-learning data-science nlp computer-vision machine-learning data-science computer-vision time-series python windows automl ensemble-learning hyperparameter-optimization tabular-data time-series-forecasting transfer-learning pytorch scikit-learn natural-language-processing linux macos gpu

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markdown · JSON · MCP: product_card(name="autogluon/autogluon")