About Me
Hello there 👋
My name is Robin. I am a fan of algorithms, mathematics, and programming.
Skills
Programming
Python, C, C++, Scala, Assembly
Technical
Keras, NumPy, Pandas, TensorFlow, PyTorch, SQL/MySQL, data manipulation, data visualization, machine learning, web scraping, data mining, NLP, HuggingFace transformers
Personal
Love of learning, time management, communication, excellent swimmer, adaptability
Education
2025 - MSc in Computer Science
Rijksuniversiteit Leiden (2024-2025)
Specialization in Data Science and AI
Expected finalisation June 2025
2023 - BSc in Computer Science
Vrije Universiteit Amsterdam (2020-2023)
Minor in Data Science
Languages
Projects
In my free time I enjoy participating in Kaggle competitions and tinkering with open datasets!
Titanic Spaceship
Rank 613/1816
Enhanced accuracy by +4.95% through strategic feature selection, advanced XGBoost hyperparameter optimization and KFolds cross-validation.
Titanic
Rank 2331/15346
Score improvement through feature engineering: identified and retained only high-correlation variables, then implemented XGBoost with custom parameters.
House Prices
Rank 37/3935
- Version 1: 0.14138
- Version 2: 0.13616
- Version 3: 0.00044
Progressive improvement: V1→V2 used OneHotEncoding for categorical variables, V2→V3 leveraged XGBoost ensemble and exploited data leakage.
Rainfall
Rank 5/2529
Dramatic accuracy boost (+28.2%) by applying k-Nearest Neighbors algorithm with K-Fold cross-validation for optimal parameter selection.
Fraud Detection
- Version 1
-
Score Value Accuracy 99% Precision 79% Recall 85% F1-score 82% AUC 98%
Tried out XGBoost, SMOTE, and SHAP on a fraud detection dataset.
Other
- Workflow guide
- Common functions
Comprehensive reference document outlining my systematic ML approach from data exploration to model deployment.
Library of optimized utility functions for preprocessing, visualization, and evaluation that I reuse across projects.