Amazon SageMaker Autopilot vs LightAutoML
Amazon SageMaker Autopilot
aws.amazon.comLightAutoML
lightautoml.readthedocs.ioSide by side
| Figure | Amazon SageMaker Autopilot | LightAutoML |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | — |
| Self-hosted | — | Yes |
| Plans published | 5 | 1 |
| Spec score · AutoML Software | 8.7 (#3) | 7.6 (#16) |
| Integrations | Reviewer evidence describes integrations with Amazon S3, IAM, CloudWatch and ECR, while AWS documents Studio and Canvas integration. | The project offers optional installation extras for NLP, computer vision, and reports, and its tutorial demonstrates a SQL data source. |
| Purpose | Autopilot automatically creates machine learning models with full visibility and is now in SageMaker Canvas. | LightAutoML is an open-source Python library for automated machine learning on tabular and text data. |
| Security | AWS describes its cloud security approach as combining security of the cloud infrastructure with security in the cloud through customer controls. | The opened project documentation and repository pages provide no security or compliance claims. |
| Support | AWS provides support plans with proactive guidance, issue resolution, and tools. | The repository directs users to its Slack community or Telegram group for advice and GitHub issues for bug reports and feature requests. |
Plans
Amazon SageMaker Autopilot
- On-demandPriced on request
- Savings PlansPriced on request
- Amazon SageMaker AI pay-as-you-goFree
- SageMaker AI Free TierFree
- On-demand SageMaker AIPrice not published
In their own words
Amazon SageMaker Autopilot
Amazon SageMaker Autopilot has no write-up on Specifiction yet; its figures are above.
LightAutoML
LightAutoML is an open-source Python library for automated machine learning on tabular and text data. It supports binary and multiclass classification and regression, using ready-made tabular, text and WhiteBox presets or modular custom pipelines. Pipeline creation can automate data processing and typing, feature selection, hyperparameter tuning, time utilization and report creation. Documented model classes include linear models, LightGBM and CatBoost boosted trees, neural networks and a WhiteBox scorecard. Its basic tutorial says the library can handle missing values and outliers automatically. Optional installation extras cover NLP, computer vision and reports, and a tutorial demonstrates a SQL data source. Installation is through PyPI with `pip install lightautoml`; the project is licensed under Apache License, Version 2.0. The maker describes it as a way for data scientists and analysts to reduce routine data preparation and model selection work. The current package handles datasets with independent samples in each row; multitable datasets and sequences remain in progress.