
Security News
Open Source CAI Framework Handles Pen Testing Tasks up to 3,600× Faster Than Humans
CAI is a new open source AI framework that automates penetration testing tasks like scanning and exploitation up to 3,600× faster than humans.
The sslearn
library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.
pip
installationIt can be installed using Pypi:
pip install sslearn
@article{sslearn2025garrido,
title = {SSLearn: A Semi-Supervised Learning library for Python},
journal = {SoftwareX},
volume = {29},
pages = {102024},
year = {2025},
issn = {2352-7110},
doi = {https://doi.org/10.1016/j.softx.2024.102024},
author = {José L. Garrido-Labrador and Jesús M. Maudes-Raedo and Juan J. Rodríguez and César I. García-Osorio},
}
The research carried out for the development of this software has been partially funded by the Junta de Castilla y León (project BU055P20), by the Ministry of Science and Innovation of Spain (projects PID2020-119894GB-I00 and TED 2021-129485B-C43) and by the project AIM-LAC (EP/S023992 /1). The author has been a beneficiary of the predoctoral scholarship from the Ministry of Education of the Junta de Castilla y León EDU/875/2021.
FAQs
A Python package for semi-supervised learning with scikit-learn
We found that sslearn demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
CAI is a new open source AI framework that automates penetration testing tasks like scanning and exploitation up to 3,600× faster than humans.
Security News
Deno 2.4 brings back bundling, improves dependency updates and telemetry, and makes the runtime more practical for real-world JavaScript projects.
Security News
CVEForecast.org uses machine learning to project a record-breaking surge in vulnerability disclosures in 2025.