Timo Günther
Data Scientist
👋 Hello and welcome to my website! My name is Timo, and I’m a data scientist with a passion for solving complex problems using data-driven insights. Thank you for visiting, and I look forward to working with you to achieve your data goals!
Check out my resumé and portfolio below 💪🏻
Clustering BBC
Various clustering algorithms were applied to a corpus of BBC news articles, and the results were compared. Furthermore, which algorithm was best suited for the assignment of the individual news categories was classified.
Clustering Music Genre
This project aimed to apply different clustering methods to a corpus of song lyrics and clarify whether or not music genres can be distinguished based on song lyrics alone.
Creating functional Prototype for Chefkoch.de
A functional prototype for a more user-friendly version of the Chef website was created, and an SQL database was integrated. The prototype had to have specific functions, such as a login, registration, and search bar.
Evaluating websites
This research aims to assess the student perspective regarding the websites of the University of Würzburg’s degree programs Media Communication (MK) and Human-Computer Systems (MCS).
Formula 1 web page
In this project, a website prototype was created and then subjected to a Nielsen heuristic evaluation, enabling usability assessment and user experience analysis. The obtained insights informed iterative improvements.
Harry Potter as an e-book
In this project, the book “Harry Potter and the Philosopher’s Stone” was processed from several text files into an epub file. A central component of this ebook is different variants for representing intertextual references within an ebook.
Integration of an SQL database into a website.
For this project, I designed a dedicated website highlighting German football champions. This site seamlessly links to an SQL database, enabling easy expansions through user interactions.
Word Embeddings
The central aim of this project is to ascertain the viability of utilizing BERT for detecting alterations in word meanings over time. This endeavour involves a comprehensive investigation that includes the utilization and comparative analysis of both Word2Vec and BERT models.