Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

Fast and Accurate ML in 3 Lines of Code

Latest Release Conda Forge Python Versions Downloads GitHub license Discord Twitter Continuous Integration Platform Tests

Installation | Documentation | Release Notes

AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on image, text, time series, and tabular data.

💾 Installation

AutoGluon is supported on Python 3.8 - 3.11 and is available on Linux, MacOS, and Windows.

You can install AutoGluon with:

pip install autogluon

Visit our Installation Guide for detailed instructions, including GPU support, Conda installs, and optional dependencies.

:zap: Quickstart

Build accurate end-to-end ML models in just 3 lines of code!

from autogluon.tabular import TabularPredictor
predictor = TabularPredictor(label="class").fit("train.csv")
predictions = predictor.predict("test.csv")
AutoGluon Task Quickstart API
TabularPredictor Quick Start API
MultiModalPredictor Quick Start API
TimeSeriesPredictor Quick Start API

:mag: Resources

Hands-on Tutorials / Talks

Below is a curated list of recent tutorials and talks on AutoGluon. A comprehensive list is available here.

Title Format Location Date
:tv: AutoGluon 1.0: Shattering the AutoML Ceiling with Zero Lines of Code Tutorial AutoML Conf 2023 2023/09/12
:sound: AutoGluon: The Story Podcast The AutoML Podcast 2023/09/05
:tv: AutoGluon: AutoML for Tabular, Multimodal, and Time Series Data Tutorial PyData Berlin 2023/06/20
:tv: Solving Complex ML Problems in a few Lines of Code with AutoGluon Tutorial PyData Seattle 2023/06/20
:tv: The AutoML Revolution Tutorial Fall AutoML School 2022 2022/10/18

Scientific Publications

Articles

Train/Deploy AutoGluon in the Cloud

:pencil: Citing AutoGluon

If you use AutoGluon in a scientific publication, please refer to our citation guide.

:wave: How to get involved

We are actively accepting code contributions to the AutoGluon project. If you are interested in contributing to AutoGluon, please read the Contributing Guide to get started.

:classical_building: License

This library is licensed under the Apache 2.0 License.

Metadata

Release files for autogluon.tabular 1.1.1b20240518

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for autogluon.tabular 1.1.1b20240518
File Size Uploaded
autogluon.tabular-1.1.1b20240518.tar.gz 260.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for autogluon.tabular 1.1.1b20240518
File Interpreter ABI Platform
autogluon.tabular-1.1.1b20240518-py3-none-any.whl Python 3 none any Details

Total release size: 570.3 kB

Release files / autogluon.tabular-1.1.1b20240518.tar.gz

Download URL autogluon.tabular-1.1.1b20240518.tar.gz
Size 260.6 kB
Tags Source
SHA-256 checksum
How to use checksums
fa857ca2bc95322baacc53674ae4fa5e13910f746662bd8ced3ce23f32767342
BLAKE2b-256 checksum
How to use checksums
cd1ad67f081e455ad043affe2e8ed40660b2536bb8aaab461ed331950d9e9fcb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.0 CPython/3.8.18

Release files / autogluon.tabular-1.1.1b20240518-py3-none-any.whl

Download URL autogluon.tabular-1.1.1b20240518-py3-none-any.whl
Size 309.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b30b6df2d2a64e4275a6130ce1645b98c4c5e201bd15d83b0829d7c52f0171bc
BLAKE2b-256 checksum
How to use checksums
7c35887b3b7bf567e3aa540335899016bd7f05882b86c2401584a8b7d16a1827
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.0 CPython/3.8.18

Release history Release notifications | RSS feed

1.6.3

2 release files

1.6.2

2 release files

1.6.1

2 release files

1.6.0

2 release files

1.5.0

2 release files

1.4.0

2 release files

1.3.1

2 release files

1.3.0

2 release files

1.2

2 release files

1.1.1

2 release files

This release

1.1.1b20240518 This release

2 release files

1.1.0

2 release files

1.0.0

2 release files

0.8.3

2 release files

0.8.2

2 release files

0.8.1

2 release files

0.8.0

2 release files

0.7.0

2 release files

0.6.2

2 release files

0.6.1

2 release files

0.6.0

2 release files

0.5.3

2 release files

0.5.2

2 release files

0.5.1

2 release files

0.5.0

2 release files

0.4.3

2 release files

0.4.2

2 release files

0.4.1

2 release files

0.4.0

2 release files

0.3.1

2 release files

0.3.0

2 release files

0.2.0

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page