Tabular Prediction

For standard datasets that are represented as tables (stored as CSV file, parquet from database, etc.), AutoGluon can produce models to predict the values in one column based on the values in the other columns. With just a single call to fit(), you can achieve high accuracy in standard supervised learning tasks (both classification and regression), without dealing with cumbersome issues like data cleaning, feature engineering, hyperparameter optimization, model selection, etc.

Quick Start Using FITtabular-quickstart.html

Quick tutorial on fitting models with tabular datasets.

In-depth FIT Tutorialtabular-indepth.html

In-depth tutorial on controlling various aspects of model fitting.

Kaggle Tutorialtabular-kaggle.html

How to use AutoGluon for Kaggle competitions.

Explore Models for Data Tables with Text and Categorical Featurestabular-multimodal-text-others.html

Tutorial about how to use autogluon to solve tasks that contain both text and categorical features.

FAQtabular-faq.html

Frequently Asked Questions