Statements (34)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:software
|
| gptkbp:category |
data science tools
machine learning tools parallel computing libraries |
| gptkbp:documentation |
https://joblib.readthedocs.io/
|
| gptkbp:feature |
easy integration with scikit-learn
fast disk-caching memory mapping of large numpy arrays robustness to process crashes simple parallelization transparent disk-caching of functions and classes |
| gptkbp:importName |
gptkb:joblib
|
| gptkbp:latestReleaseVersion |
1.3.2
|
| gptkbp:license |
gptkb:BSD_License
|
| gptkbp:maintainedBy |
gptkb:Joblib_developers
|
| gptkbp:pipInstall |
pip install joblib
|
| gptkbp:programmingLanguage |
gptkb:Python
|
| gptkbp:releaseDate |
2023-10-10
|
| gptkbp:repository |
https://github.com/joblib/joblib
|
| gptkbp:supports |
Python functions
custom objects numpy arrays |
| gptkbp:usedBy |
gptkb:scikit-learn
|
| gptkbp:usedFor |
parallel computing
caching results of function calls efficient serialization of Python objects lightweight pipelining in Python |
| gptkbp:bfsParent |
gptkb:Joblib_developers
gptkb:Optuna gptkb:Databricks_Runtime_11.2_ML gptkb:Databricks_Runtime_14.x_ML gptkb:Databricks_Runtime_15.x_ML |
| gptkbp:bfsLayer |
8
|
| https://www.w3.org/2000/01/rdf-schema#label |
Joblib
|