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/0.3.2/modelkit-0.3.2.tbz sha256=a0335f799da12302a0568320b5f5c4c26c531a336740fea07f326cb2729ae8ac sha512=bc692df9c0a868f99c14159c03c0c975d6fd51d6283a0e8491197abde8cebcd04f26ba990b66dc3ac711ab01bc8f7c2a4279fdf5b30a64ded5f622e0b2bcc630 |
| Edit | https://github.com/ocaml/opam-repository/tree/master/packages/modelkit/modelkit.0.3.2/opam |
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