{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/7"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/5"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"},{"label":"Image Recognition","url":"https://skillfed.io/packages/category/scientific-engineering-image-recognition"}],"enrichment":{"capability":"Automates machine learning model training and prediction on tabular data with minimal code, handling feature engineering, algorithm selection, and hyperparameter tuning internally.","skillfed_tags":["automl","tabular-data","aws-maintained"],"use_cases":["Build a classification model for customer churn prediction from historical transaction and demographic data in minutes.","Rapidly prototype a regression model for sales forecasting without manual feature selection or algorithm tuning.","Deploy a production ML pipeline for fraud detection by fitting a model on labeled historical transactions.","Compare multiple baseline models on a new tabular dataset to establish performance benchmarks quickly.","Automate model retraining on fresh data with minimal code changes in a scheduled batch pipeline."],"what_it_does":"AutoGluon Tabular is an automated machine learning library that trains and deploys high-accuracy predictive models on structured (tabular) data with minimal user code. It abstracts away the typical ML workflow\u2014data preprocessing, feature engineering, algorithm selection, and hyperparameter tuning\u2014so you can fit and predict in just a few lines. The package is built on top of numpy, scipy, pandas, and scikit-learn, and integrates networkx for graph-based feature interactions and autogluon.core and autogluon.features for its automation engine.\n\nThe library is designed for developers and data scientists who want to quickly build production-ready models without deep expertise in tuning individual algorithms. It supports classification and regression tasks on tabular data, and is part of the broader AutoGluon ecosystem (which also handles time series and multimodal data). The package is actively maintained by AWS AI, supports Python 3.10\u20133.13 across Linux, macOS, and Windows, and carries an Apache-2.0 license.","worth_installing":"Yes. The package is actively maintained, has low install friction, carries a permissive license, and solves a real problem\u2014reducing the time and expertise needed to train tabular ML models. It is well-suited for rapid prototyping, production deployment, and learning. No known security vulnerabilities as of the query date."},"id":"autogluon-tabular","links":{"html":"https://skillfed.io/packages/autogluon-tabular","md":"https://skillfed.io/packages/autogluon-tabular.md","pypi":"https://pypi.org/project/autogluon-tabular/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-06","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"autogluon.tabular","python_support":"supports_current","summary":"Fast and Accurate ML in 3 Lines of Code"},"popularity":{"monthly_downloads":569878,"position":5957,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.6.1"}