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Name: Rikke Uldbæk
Type: User
Name: Rikke Uldbæk
Type: User
This repository contains assignment 1 which is a part of the portfolio exam in the course Language Analytics at Aarhus University.
This repository contains assignment 2 which is a part of the portfolio exam in the course Language Analytics at Aarhus University.
This repository contains assignment 3 which is a part of the portfolio exam in the course Language Analytics at Aarhus University.
This repository contains assignment 4 which is a part of the portfolio exam in the course Language Analytics at Aarhus University.
This repository contains assignment 1 which is a part of the portfolio exam in the course Visual Analytics at Aarhus University.
This repository contains assignment 2 which is a part of the portfolio exam in the course Visual Analytics at Aarhus University.
This repository contains assignment 3 which is a part of the portfolio exam in the course Visual Analytics at Aarhus University.
Main repository for all code and data related to Language Analytics (F23)
Repository for exercises in spatial analytics 2021 and 2022
Main repository for all code and data related to Visual Analytics (F22)
This repository contains the data analysis and statistical analysis of the cognitive neuroscience exam paper.
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.
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.
Teaching for the course Methods 3: Multilevel Statistical Modeling and Machine Learning at Aarhus University, autumn semester 2021
R notes
:exclamation: This is a read-only mirror of the CRAN R package repository. LMest — Generalized Latent Markov Models
Methods 4: Bayesian Computational Modelling
Network analysis on twitter echo-chambers with polarised opinions about #prolife and #prochoice
Statistical Rethinking course and book package
This repository is for educational purposes only.
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.
Portfolios
Neuro science
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).
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.