open   documented  

Scikit-learn

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 BoisberrangerJoris Van den BosscheLoïc EstèveThomas J. FanAlexandre GramfortOlivier GriselYaroslav HalchenkoNicolas HugAdrin JalaliJulien JerphanionGuillaume LemaitreChristian LorentzenJan Hendrik MetzenAndreas MuellerVlad NiculaeJoel NothmanHanmin QinBertrand ThirionTom Dupré la TourGael VaroquauxNelle VaroquauxRoman Yurchak
Updated:  2022-01-18
Source:  https://scikit-learn.org/stable/
Keywords:  machine-learningPythonprogrammingclustering

open   documented  

MNE-Python

Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data: MEG, EEG, sEEG, ECoG, NIRS, and more.

Authors:  Alexandre GramfortMartin LuessiEric LarsonDenis A. EngemannDaniel StrohmeierChristian BrodbeckRoman GojMainak JasTeon BrooksLauri ParkkonenMatti S. Hämäläinen
Updated:  2021-12-02
Source:  https://mne.tools/stable/index.html
Keywords:  experimentPythondatamachine-learningneuroscience