core
ML vocabulary
Develops and maintains a standard ontology of machine learning concepts and their relationships with other vocabularies and ontologies
📚 CORE ontology of ML-Schema and mapping to other machine learning vocabularies and ontologies (DMOP, Exposé, OntoDM, and MEX)
27 stars
14 watching
8 forks
Language: HTML
last commit: about 4 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
| A Python library for scalable machine learning using Dask alongside popular ML libraries | 907 |
| A Clojure machine learning library providing idiomatic and harmonized support for various classification, regression, clustering, and unsupervised models. | 220 |
| Implementations of basic machine learning algorithms in Haskell | 57 |
| A Clojure-based machine learning library that provides a simple and stable way to perform regression and classification tasks. | 97 |
| A framework to standardize intercomponent schemas for multi-stage machine learning pipelines | 7 |
| Enables machine learning with scikit-learn in OCaml | 34 |
| A high-performance statistical machine learning library written in Common Lisp | 261 |
| A proof-of-concept implementation of decentralized machine learning on top of the Golem architecture | 43 |
| A Clojure library for building machine learning models on top of Weka and other algorithms | 135 |
| A library for recording and managing metadata associated with machine learning workflows | 629 |
| A comprehensive solution to machine learning assignments on Coursera with MATLAB code | 55 |
| Provides an infrastructure for machine learning in R, enabling users to focus on experiments without writing lengthy wrappers and boilerplate code. | 1,648 |
| A machine learning library written in Lisp (Clojure) providing simple implementations of various algorithms and utilities. | 76 |
| An all-in-one web-based IDE for machine learning and data science | 3,446 |
| Provides an object-oriented framework for efficient machine learning in R | 952 |