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Description:

autogluon.common 1.1.1

Fast and Accurate ML in 3 Lines of Code

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

MultiModalPredictor

TimeSeriesPredictor

: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

AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data (Arxiv, 2020) (BibTeX)
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation (NeurIPS, 2020) (BibTeX)
Benchmarking Multimodal AutoML for Tabular Data with Text Fields (NeurIPS, 2021) (BibTeX)
XTab: Cross-table Pretraining for Tabular Transformers (ICML, 2023)
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting (AutoML Conf, 2023) (BibTeX)
TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications (Under Review, 2024)

Articles

AutoGluon-TimeSeries: Every Time Series Forecasting Model In One Library (Towards Data Science, Jan 2024)
AutoGluon for tabular data: 3 lines of code to achieve top 1% in Kaggle competitions (AWS Open Source Blog, Mar 2020)
AutoGluon overview & example applications (Towards Data Science, Dec 2019)

Train/Deploy AutoGluon in the Cloud

AutoGluon Cloud (Recommended)
AutoGluon on SageMaker AutoPilot
AutoGluon on Amazon SageMaker
AutoGluon Deep Learning Containers (Security certified & maintained by the AutoGluon developers)
AutoGluon Official Docker Container
AutoGluon-Tabular on AWS Marketplace (Not maintained by us)

: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.