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Xannadoo/README.md

Hej ๐Ÿ‘‹

I'm Chrisanna, also known as Sanna.

๐Ÿ‘ฉโ€๐ŸŽ“ I completed my MSc in Data Science at ITU Copenhagen in late 2025, with a focus on explainability of LLMs, and machine learning models in general.

๐Ÿง  I am interested in knowing why. More specifically, why do machine learning models make the decisions they do/return the response they did? How do we go about creating these explanations and how reliable are the explanations? What can we trust and how much can we trust it? What do we even mean by that anyway?

๐ŸŽ† Fun fact: The name Xannadoo comes from Samuel Taylor Coleridge's poem Kubla Khan. Many years ago, a collegue of mine misheard my name and it stuck. I also used to live in Ottery St Mary, the birthplace of Coleridge, before moving to Denmark in 2020.

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  1. examining-faithfulness-COT-deepseekR1 examining-faithfulness-COT-deepseekR1 Public

    Examining the Faithfulness of Deepseek R1โ€™s Chain-of-Thought Reasoning

    Jupyter Notebook

  2. comparision-reasoning-skills-llm comparision-reasoning-skills-llm Public

    Investigating Comparison Reasoning Skills in a Large Language Model

    Jupyter Notebook

  3. carbonCostKaggle/carbon-cost-kaggle carbonCostKaggle/carbon-cost-kaggle Public

    Investigating the carbon cost of machine learning competitions that use medical image datasets.

    Jupyter Notebook 1