Pinned Repositories
care-ml
CARE-ML: Predicting the use of restraint on psychiatric inpatients using EHRs and ML. Developed by sarakolding and signekb for their Master's Thesis.
Programming-for-Humanities-A-Digital-Learning-Platform
seedcase-sprout
Upload your research data to formally structure it for better, more reliable, and easier research.
autoDocstring
VSCode extension that generates docstrings for python files
Classifying-Breast-Cancer-from-Mammograms-Using-CNNs-and-Transfer-Learning
This repository contains code for classifying breast cancer from DDSM / CBIS-DDSM mammograms
conventionalcommits.org
The conventional commits specification
data-science-course
DaWinoBias-Assessing-Occupational-Gender-Stereotypes-in-Danish-NLP-Models
frictionless-py
Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data
osdc
Open-Source Diabetes Classifier: an R package to classify diabetes status in Danish registers
signekb's Repositories
signekb/AdvancedR
"Learning advanced R!"
signekb/autoDocstring
VSCode extension that generates docstrings for python files
signekb/Classifying-Breast-Cancer-from-Mammograms-Using-CNNs-and-Transfer-Learning
This repository contains code for classifying breast cancer from DDSM / CBIS-DDSM mammograms
signekb/data-science-course
signekb/DaWinoBias-Assessing-Occupational-Gender-Stereotypes-in-Danish-NLP-Models
signekb/frictionless-py
Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data
signekb/methods-2-course
Methods 2: The General Linear Model
signekb/National-gender-inequality-and-the-conditional-cooperation-schema
signekb/NLP-E21
This repository acts as the main reference point for Natural Language Processing (Fall '21) as part of the kandidatuddannelsen in Cognitive Science at Aarhus University.
signekb/Scientific-Computing-Workshop-E21
A 3 day workshop on scientific computing with Python assuming previous experience with programming and going through object-oriented programming, numpy and basic linear algebra and finally implementing a simple neural network.