Jona Sassenhagen
jona-sassenhagen
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Materials for workshops on the open neural time series analysis toolbox MNE-Python
Python for Psychologists teaching materials
Code, text and shiny app underlying our Brain & Language paper (Sassenhagen & Alday, 2016) on a common mistake in covariate control for statistical analysis of cognitive/linguistic experiments
Public Charvis analysis scripts
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Materials for workshops on the open neural time series analysis toolbox MNE-Python
Python for Psychologists teaching materials
Public Charvis analysis scripts
Gunnar's 1 Billion Row Challenge (Python)
Declarative statistical visualization library for Python
Mastering Diverse Domains through World Models
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
⚡ Building applications with LLMs through composability ⚡
Code for What Drug Was That?
torch-optimizer -- collection of optimizers for Pytorch
A library of sklearn compatible categorical variable encoders
A game theoretic approach to explain the output of any machine learning model.
General purpose unsupervised sentence representations
Transforms PDF, Documents and Images into Enriched Structured Data
Clone of a foundry repository to train and score models.
Python package for covariance matrices manipulation and Biosignal classification
Generate custom Docker and Singularity images, and minimize existing containers.
Ultimate transformation library that supports validation, contexts and aiohttp.
Code, text and shiny app underlying our Brain & Language paper (Sassenhagen & Alday, 2016) on a common mistake in covariate control for statistical analysis of cognitive/linguistic experiments
Code for my Language and Cognitive Processes paper on distributed-lags regression modelling for language-associated brain data
Frankfurt Psychology Department Open Science Initiative
MNE Code Sprint 2019 @ Hosted at Facebook
Tinkering with Git and ML