Deepchecks tests and validates machine learning models and data, covering workflows from research through production.
Open source
24 alternativesHow do DVC and Ludwig compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | DVC | Ludwig |
|---|---|---|
| What it is | Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments. | Ludwig provides a low code framework for building custom LLMs, neural networks, and other AI models. |
| Website | ||
| Type | Online tool | Open-source project |
| Topic | ||
| Pricing | Not confirmed | Not confirmed |
| Platforms | Web | Not recorded |
| Open source | Not stated | Yes |
| Language | English | English |
| Alternatives |
Sites similar to both DVC and Ludwig.
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.
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
TPOT uses genetic programming to optimize machine learning pipelines in Python.
Ray provides an AI compute engine with a distributed runtime and libraries for machine learning workloads.