BSc student (AI & Data) at the Technical University of Denmark. I work on ML pipelines, LLM evaluation, and data-centric NLP.

• Degree: BSc in Artificial Intelligence & Data @ DTU (2/3 years completed)
• Average grade: 9.8 (Danish 7-point scale)
• Interests: Machine Learning, Reinforcement Learning, NLP
• Location: Copenhagen, Denmark
• CV (PDF): View here
• Email: david.lindah@gmail.com

Multilingual classification of Danish educational texts, with a custom data pipeline and LLM evaluation framework.
Tech: Python, PyTorch/Transformers, scikit-learn, Pandas
Impact: Demonstrates practical NLP pipeline development and evaluation — useful for educational content analysis and automated classification tasks.

End-to-end analysis of urinary test data to predict kidney stone-related conditions. Includes preprocessing, EDA, modeling, and visualizations.
Tech: Python, Pandas, Matplotlib, scikit-learn
Impact: Shows ability to handle structured medical datasets, extract insights, and communicate results visually.

Playground for experimenting with Bayesian Optimization on various objective functions.
Tech: Python, scikit-learn, NumPy, Matplotlib
Impact: Highlights skills in hyperparameter tuning, optimization techniques, and experiment tracking.

Regression modeling of solar panel energy output based on environmental factors.
Tech: Python, Pandas, Matplotlib, scikit-learn
Impact: Combines regression modeling with renewable energy data, demonstrating applied ML in the sustainability domain.

• Programming: Python, Git
• ML / Data: Pandas, NumPy, scikit-learn, PyTorch, Matplotlib
• Other: LaTeX

Mathematics (calculus, linear algebra, differential equations), Programming, Statistics, Signals & Data RL & Control.

• Danish Educational LLM Classifier
• Kidney Stone Urine Analysis
• BayesOpt Playground
• Solar Power Regression