Advanced Tabular TutorialsΒΆ

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.

Multi-Label Prediction

How to predict multiple columns in a data table.

tabular-multilabel.html
Kaggle Tutorial

Using AutoGluon for Kaggle competitions with tabular data.

tabular-kaggle.html
Training models with GPU support

How to train models with GPU support.

tabular-gpu.html
Adding a Custom Metric

How to add a custom metric to AutoGluon.

tabular-custom-metric.html
Adding a Custom Model

How to add a custom model to AutoGluon.

tabular-custom-model.html
Adding a Custom Model (Advanced)

How to add a custom model to AutoGluon (Advanced).

tabular-custom-model-advanced.html
Deployment Optimization

Tutorial on optimizing the predictor artifact for production deployment.

tabular-deployment.html