Lightwood builds and customizes machine learning pipelines using a declarative JSON-AI syntax.
Open source
24 alternativesHow do EvalML and AutoGL compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | EvalML | AutoGL |
|---|---|---|
| What it is | EvalML builds, optimizes, and evaluates machine learning pipelines with automated data checks and objective functions. | AutoGL provides automated graph learning through a machine learning framework and toolkit. |
| 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 EvalML and AutoGL.
Lightwood builds and customizes machine learning pipelines using a declarative JSON-AI syntax.
Detecto supports building and training computer vision models with the PyTorch machine learning framework.
ML_Forgex trains, evaluates, and predicts with machine learning models on cleaned datasets.
Karate Club offers algorithms for unsupervised learning on graph data in Python.
Katib automates machine learning on Kubernetes, including hyperparameter tuning and neural architecture search.
Auto_ViML builds multiple machine learning models with a single line of code.