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/0.2.1/modelkit-0.2.1.tbz sha256=ec5be6fc4f47f7a73fae676e730b9c66400327320231a61f0d2044d8d46aab59 sha512=e63baf8958b95f9b57f27ae42c6fb434674db18d278af7d60b74cac239407cddef57a16fab99101c9087561f9c7d826340505f449e99629c86f708ab89840946 |
| Edit | https://github.com/ocaml/opam-repository/tree/master/packages/modelkit/modelkit.0.2.1/opam |
No package is dependent
