Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
Open source
24 alternativesHow do Aim and Ray compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | Aim | Ray |
|---|---|---|
| What it is | Aim tracks machine learning experiments and describes itself as an open-source experiment tracker. | Ray provides an AI compute engine with a distributed runtime and libraries for machine learning workloads. |
| 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 Aim and Ray.
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
TPOT uses genetic programming to optimize machine learning pipelines in Python.
The Feast repository describes an open source feature store for AI and machine learning projects.
Deepchecks tests and validates machine learning models and data, covering workflows from research through production.
The Datumbox framework is written in Java for developing machine learning and statistical applications.
Evidently evaluates, tests, and monitors machine learning systems and data pipelines.