AutoGluon enables easy-to-use and easy-to-extend AutoML with a focus on automated stack ensembling, deep learning, and real-world applications spanning image, text, and tabular data. Intended for both ML beginners and experts, AutoGluon enables you to quickly prototype deep learning and classical ML solutions for your raw data with a few lines of code. Automatically utilize state-of-the-art techniques (where appropriate) without expert knowledge. Leverage automatic hyperparameter tuning, model selection/ensembling, architecture search, and data processing. Easily improve/tune your bespoke models and data pipelines, or customize AutoGluon for your use-case. AutoGluon is modularized into sub-modules specialized for tabular, text, or image data. You can reduce the number of dependencies required by solely installing a specific sub-module via: python3 -m pip install <submodule>.
Features
- The default installation of autogluon.tabular standalone is a skeleton installation
- Install via pip install autogluon.tabular[all] to get the same installation of tabular as via pip install autogluon
- Available optional dependencies: lightgbm,catboost,xgboost,fastai. These are included in all
- Optional dependencies not included in all: vowpalwabbit
- To run autogluon.tabular with only the optional LightGBM and CatBoost models
- Experimental optional dependency