Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
Open source
24 alternativesHow do Deepchecks and Notebooks compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | Deepchecks | Notebooks |
|---|---|---|
| What it is | Deepchecks tests and validates machine learning models and data, covering workflows from research through production. | This Docker-based starter kit provides a runtime for machine learning work in Jupyter notebooks. |
| Website | ||
| Type | Open-source project | Open-source project |
| Topic | ||
| Pricing | Not confirmed | Not confirmed |
| Platforms | Not recorded | Not recorded |
| Open source | Yes | Yes |
| Language | English | English |
| Alternatives |
Sites similar to both Deepchecks and Notebooks.
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
TPOT uses genetic programming to optimize machine learning pipelines in Python.
The Datumbox framework is written in Java for developing machine learning and statistical applications.
PrimeHub offers an open-source platform for managing machine learning operations and workflows.
MLRun provides an open-source MLOps platform for managing machine learning applications, pipelines, and CI/CD delivery.
Evidently evaluates, tests, and monitors machine learning systems and data pipelines.