Our verdict
We have not reviewed EvalML yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About EvalML
EvalML is an open-source AutoML library for Python. It automates the process of building, tuning, and evaluating machine learning models. The library provides a unified interface for common tasks like data splitting, feature engineering, and model selection.
Best for
Data scientists who want to rapidly prototype and compare models without writing extensive code.
Use cases
- Automating model selection for classification and regression tasks
- Quickly prototyping machine learning pipelines
- Comparing multiple algorithms with minimal code
Notes
849 stars on GitHub. Last updated 2026-01-14. Licensed BSD-3-Clause.
Pros
- Simplifies the machine learning workflow with a high-level API
- Supports a variety of algorithms and preprocessing steps
- Open-source with community contributions
Cons
- Limited to supervised learning tasks
- May not handle very large datasets efficiently
- Less flexible than manual tuning for complex problems
Key facts
What we have checked
- Latest version
- 0.84.0 (released 6 June 2024)
- GitHub stars
- 850
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How EvalML is growing
849 to 850
Sources
Where this comes from
- GitHubOfficial
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
Released 0.84.0
Released 0.83.0
Released 0.82.0
Released 0.81.1
Released 0.81.0
Released 0.80.0
Released 0.79.0
Released 0.78.0
Released 0.77.0
Released 0.76.0
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