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Rikke Uldbæk's Projects

cds-language icon cds-language

Main repository for all code and data related to Language Analytics (F23)

cds-spatial icon cds-spatial

Repository for exercises in spatial analytics 2021 and 2022

cds-visual icon cds-visual

Main repository for all code and data related to Visual Analytics (F22)

cognitive_neuroscience icon cognitive_neuroscience

This repository contains the data analysis and statistical analysis of the cognitive neuroscience exam paper.

dadjokegenerator_la_fp icon dadjokegenerator_la_fp

This repository contains the final project in the course Language Analytics which is a part of the elective Cultural Data Science at Aarhus University. In this final project two text-generators producing dad-jokes are compared, namely a finetuned and pretrained GPT-2 and a simple RNN.

discoveraarhus icon discoveraarhus

This repository contains the final project in the course Spatial Analytics which is a part of the elective Cultural Data Science at Aarhus University. In this project we have designed a map application which helps individuals and tourists explore the city of Aarhus.

github_methods_3 icon github_methods_3

Teaching for the course Methods 3: Multilevel Statistical Modeling and Machine Learning at Aarhus University, autumn semester 2021

lmest icon lmest

:exclamation: This is a read-only mirror of the CRAN R package repository. LMest — Generalized Latent Markov Models

skincancerclassifier_va_fp icon skincancerclassifier_va_fp

This repository contains the final project of the course Visual Analytics which is a part of the elective Cultural Data Science at Aarhus University. In this final project a skin cancer classifier has been build in order to segment and classify a collection of dermatoscopic images in to seven types of skin cancer.

uldbaek-paaby-bachelor2022 icon uldbaek-paaby-bachelor2022

Scripts used in bachelor thesis in Cognitive Science WLatent Transition Analysis by Latent Markov models are employed to longitudinal data of language acquisition in Danish children, by the R package Lmest (Bartolucci et al., 2017).

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