modelkitversion Documentation on ocaml.org
Portable classical machine learning workflows for OCaml
ModelKit is a native OCaml library for cohesive classical machine learning workflows. It is designed around immutable estimator specifications, leakage-safe pipelines, deterministic evaluation, and portable fitted artifacts.
| Tags | data-science machine-learning |
|---|---|
| Author | Asara |
| License | Apache-2.0 |
| Published | |
| Homepage | https://github.com/asara-io/ModelKit |
| Issue Tracker | https://github.com/asara-io/ModelKit/issues |
| Maintainer | Asara developers <devs@asara.io> |
| Dependencies | |
| Source [http] | https://github.com/asara-io/ModelKit/releases/download/0.6.3/modelkit-0.6.3.tbz sha256=a70c1c95bdc13e7abff028394a14300e2847e3f3931d6e1476394cbcdfb05407 sha512=eb186a5a919a43006ea350e8ab49845d230dc1de8f61d83c06f4d1aa2371930ea0239dcf9dbb3337e18867301422c6dc5af4d569afaf187bde5d1a2368b7bbe4 |
| Edit | https://github.com/ocaml/opam-repository/tree/master/packages/modelkit/modelkit.0.6.3/opam |
Required by
- modelkit-nx>=0.6.3
- modelkit-parallel>=0.6.3
- modelkit-talon>=0.6.3
- modelkit-xgboost
