Welcome to my student repo at IT-University (ITHS) where I studied AI and Machine Learning (Aug 2022-May 2024).
I am an engineer and experienced project manager with a background in product development within medical technology and cutting tools. My main focus has always been to create an environment, which enables my team members to perform at their best. I am good at creating clear structures, motivating others and communication. I am result- and solution oriented and put my efforts where I can create most value. I am also curious and always interested in expanding my knowledge, which has led me to study AI and machine learning. I am very excited about this new step and eager to transition my career into the tech industry, where I want to make a real difference.
My studies of AI and ML at IT-University were a good complement to my theoretical background as an engineer and were very hands-on, which suited me well. From my studies I have experience with cleaning and preparing both image and text data with for example Pandas, Spacy, NLTK; building and evaluating models in frameworks such as TensorFlow/Keras, PyTorch, scikit-learn for ML and Deep ML (from scratch or with transfer learning). I have also experience in Data Engineering: ELT/ETL, CI/CD with GitHub Actions, Docker and pipelines in Airflow. During my internships I focused mainly on text data, for example analysis of domain-specific, non-annotated text, working with concepts such as BERT-models, unsupervised clustering and labeling techniques, zero-shot classification, and active learning. Futhermore I have extensively explored potential of small LLMs and various strategies to constrain and structure their output. Finally I have finetuned models for custom object detection (Paliscope property). This hands-on experience contributed to the ongoing development, bringing ideas closer to tangible products.
| Repo | Description | Note |
|---|---|---|
| Diploma project | exploration of strategies to constrain and structure output from small local LLMs | my own project in collaboration with supervisor |
| Deep ML - project | building GRU model and hyperparameter tuning for text classification (Tensorflow, Scikit-learn ) | my own work |
| Deep ML - RNN lab | (a) building RNN/GRU/LSTM for text classification (TensorFlow, Scikit-learn), (b) additional work on transfer learning (Huggingface/transformers, KerasNLP) | my own work |
| Deep ML - CNN lab | (a) building CNN for image classification, (b) tranfer learning and hyperparemeter tuning (TensorFlow, Scikit-learn) | my own work |
| Paliscope - proj2 | active learning of ML models on blog posts | short explorative task during internship |
| Paliscope - proj1 | unsupervised text clustering and labeling (NLP, BERT, UMAP, HDBSCAN, TF-IDF) | short explorative task during internship |
| Data engineering - proj | ELT, LLM, docker, airflow, dashboard | group effort, my contribution ci/cd, docker, airflow, backend logic in collaboration |
| Databases - labs | SQL queries, build database | my own work |
| Machine learning - lab | machine learning models explored (Scikit-learn) | my own work |
| Data analysis - lab | data analysis (Pandas, Seaborn, Plotly) | my own work |
| Data analysis - project | data analysis, results in dashboard | group effort, my contribution all data analysis and call-backs code |
| Statistics - lab | statistical analysis and report (Scipy, Statmodels) | my own work |
| Python - labs | ML algorithm, OOP (NumPy, Matplotlib) | my own work |