Classical Machine Learning Frameworks
General-purpose libraries for traditional (non-deep) machine learning — regression, classification, clustering and preprocessing — embedded as code in your own application.
44 projects
See methodology for ranking rules; order uses public GitHub metrics within this scenario.
| Rank | Project | Stars | Forks | Updated | License |
|---|---|---|---|---|---|
| 41 |
xlearn
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface. |
3.1K | 516 | 08/28/23 | Apache-2.0 |
| 42 |
bolt
10x faster matrix and vector operations |
2.5K | 174 | 10/12/22 | MPL-2.0 |
| 43 |
auto_ml
[UNMAINTAINED] Automated machine learning for analytics & production |
1.7K | 309 | 02/10/21 | MIT |
| 44 |
automl-gs
Provide an input CSV and a target field to predict, generate a model + code to run it. |
1.9K | 180 | 10/22/19 | MIT |