Amazon SageMaker Autopilot vs Auto-PyTorch
Amazon SageMaker Autopilot
aws.amazon.comAuto-PyTorch
automl.github.ioSide by side
| Figure | Amazon SageMaker Autopilot | Auto-PyTorch |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Linux | — | Yes |
| API | Yes | — |
| Self-hosted | — | Yes |
| Plans published | 5 | 1 |
| Spec score · AutoML Software | 8.7 (#3) | 8.4 (#5) |
| Data preparation | It can fill missing data, provide statistical insights about dataset columns, and extract information from non-numeric columns. | For tabular tasks, its preprocessing includes imputation, categorical encoding, scaling, and feature preprocessing, with corresponding hyperparameters tuned during search. |
| Deployment | After training, users can deploy Autopilot models to real-time endpoints or run batch inference jobs. | The project provides a Docker image and can be installed from PyPI or manually in a Python environment. |
| Integrations | Reviewer evidence describes integrations with Amazon S3, IAM, CloudWatch and ECR, while AWS documents Studio and Canvas integration. | The documentation describes using Dask.distributed for parallel Bayesian optimization and sklearn column transformers for data preprocessing. |
| Purpose | Autopilot automatically creates machine learning models with full visibility and is now in SageMaker Canvas. | Auto-PyTorch is an automated machine learning toolkit based on PyTorch that automates algorithm selection and hyperparameter tuning. |
| What it does | Amazon SageMaker Autopilot automates data inspection, preprocessing, feature engineering, algorithm selection, model training, tuning, evaluation and ranking for machine-learning projects. | Auto-PyTorch is an automated machine-learning toolkit based on PyTorch that helps users automate algorithm selection and hyperparameter tuning. |
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.
Auto-PyTorch
Auto-PyTorch is a free, self-hosted machine-learning toolkit based on PyTorch. It automates algorithm selection and hyperparameter tuning, including neural-network architecture and training settings, within a user-defined search budget. Documented search methods include Bayesian optimisation, meta-learning, SMAC and Hyperband. Supported work includes tabular classification, tabular regression and time-series forecasting. Tabular preprocessing can perform imputation, categorical encoding, scaling and feature processing, while related hyperparameters are tuned. The toolkit can build ensembles from validation-set predictions, with controls for ensemble size and candidate limits. Users can set estimator memory limits and total wall time. Parallel Bayesian optimisation uses Dask.distributed; workers need shared filesystem access to training data and models. Installation documentation specifies Linux, Python 3.7 or later, a C++11-capable compiler and SWIG 3.0. SWIG 4.0 or later is unsupported. Forecasting needs extra dependencies. A Docker image and PyPI installation are documented, under the 3-clause BSD license.