Auto-PyTorch
6.1#11 in automl softwareFree planFree planLinuxSelf-hosted
VisitAuto-PyTorch vs BigML
What both publish
| Fact | Auto-PyTorch | BigML |
|---|---|---|
| Deployment | The project provides a Docker image and can be installed from PyPI or manually in a Python environment. | Private deployments can run on a preferred cloud provider, ISP, or on-premises behind a corporate firewall, as managed or self-managed deployments. |
| Integrations | The documentation describes using Dask.distributed for parallel Bayesian optimization and sklearn column transformers for data preprocessing. | Official tools include Google Sheets, Zapier, Node-RED, Alexa, PredictServer and a native BigMLX macOS application. |
Auto-PyTorch plans
- Auto-PyTorchFree
BigML plans
- FREEFree
- Basic BigML training$800, paid once
- BigML Lite$1,000 a month
- Extra Support$3,000 a month
- BigML Lite (annual)$10,000 a year
- Bronze Enterprise$45,000 a year
Pick Auto-PyTorch if…
Auto-PyTorch suits machine-learning practitioners who want to automate model search in a code-based, self-hosted workflow. Its documented tasks cover tabular data and time-series forecasting.
Pick BigML if…
BigML suits analysts, software developers, and scientists who need machine-learning tools, workflow automation, or model deployment options. Its API and language bindings may suit teams integrating models into software.