Speech and Language Resource Bank
Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, data preprocessing, model selection, model evaluation, and many other utilities.
Authors: Jérémie du Boisberranger,
Joris Van den Bossche,
Loïc Estève,
Thomas J. Fan,
Alexandre Gramfort,
Olivier Grisel,
Yaroslav Halchenko,
Nicolas Hug,
Adrin Jalali,
Julien Jerphanion,
Guillaume Lemaitre,
Christian Lorentzen,
Jan Hendrik Metzen,
Andreas Mueller,
Vlad Niculae,
Joel Nothman,
Hanmin Qin,
Bertrand Thirion,
Tom Dupré la Tour,
Gael Varoquaux,
Nelle Varoquaux,
Roman Yurchak
Updated: 2022-01-18
Source: https://scikit-learn.org/stable/
Keywords: machine-learning,
Python,
programming,
clustering
Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data: MEG, EEG, sEEG, ECoG, NIRS, and more.
Authors: Alexandre Gramfort,
Martin Luessi,
Eric Larson,
Denis A. Engemann,
Daniel Strohmeier,
Christian Brodbeck,
Roman Goj,
Mainak Jas,
Teon Brooks,
Lauri Parkkonen,
Matti S. Hämäläinen
Updated: 2021-12-02
Source: https://mne.tools/stable/index.html
Keywords: experiment,
Python,
data,
machine-learning,
neuroscience