julearn
About
The Forschungszentrum Jülich Machine Learning Library
Check our full documentation here: https://juaml.github.io/julearn/index.html
It is currently being developed and maintained at the Applied Machine Learning group at Forschungszentrum Juelich, Germany.
Installation
Use pip to install from PyPI like so:
pip install julearn
You can also install via conda, like so:
conda install -c conda-forge julearn
Licensing
julearn is released under the AGPL v3 license:
julearn, FZJuelich AML machine learning library. Copyright (C) 2020, authors of julearn.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License along with this program. If not, see http://www.gnu.org/licenses/.
Citing
If you use julearn in a scientific publication, please use the following reference
Sami Hamdan,Shammi More,Leonard Sasse,Vera Komeyer,Kaustubh R. Patil,Federico Raimondo,for the Alzheimer’s Disease Neuroimaging Initiative,Julearn: an easy-to-use library for leakage-free evaluation and inspection of ML models,Gigabyte,2024 https://doi.org/10.46471/gigabyte.113
Since julearn is also heavily reliant on scikit-learn, please also cite them: https://scikit-learn.org/stable/about.html#citing-scikit-learn
Release files for julearn 0.3.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| julearn-0.3.5.tar.gz | 2.6 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| julearn-0.3.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.9 MB
Release files / julearn-0.3.5.tar.gz
| Download URL | julearn-0.3.5.tar.gz |
|---|---|
| Size | 2.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
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PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Mar 6, 2026.
Transparency logRelease files / julearn-0.3.5-py3-none-any.whl
| Download URL | julearn-0.3.5-py3-none-any.whl |
|---|---|
| Size | 258.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
b165c57ad8fff7c17ba7ea54c3e86c01ed21c2d30160105a49fed6da1f247ce7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Mar 6, 2026.
Transparency log
