This ML project explores the possibilities of using alternative data sources such as satellite imaging, green-space estimation, crime statistics and distance-to-centre estimation. With these features we improved ML model performance significantly, leading to more accurate real estate pricing.
In this project I replicated a research paper published by Lin et al. 2021, comparing model performance and surpassing some of the original paper's metrics.
This is a collection of notebooks showcasing how to approach problems such as:
I’m graduating in June 2023 with a BSc in Business Administration, majoring in Finance. I’m hoping to pursue my lifelong passion in finance, machine learning, and data science. I’ve worked on various IT projects, including web development, algorithmic trading, and data visualization. I have 6 years of programming experience, mainly in Python, and built various ML-related projects. I enjoy collaborating with others and solving complex problems. My work ethic, attention to detail, and communication skills make me a valuable team player. Overall, I’m excited to further develop my skills and contribute to impactful projects.
Python (6 years):
Pandas, Numpy, Matplotlib, SciKit-Learn, TensorFlow, Keras, Seaborn, Streamlit
React (<1 year), SQL (<1 year), STATA (<1 year)
Universiteit van Amsterdam (UvA): BSc in Business Administration (Major in Finance)
Universitat Pompeu Fabra (UPF): Exchange student at the Faculty of Economics
Rudbecksgymnasiet: IBDP Candidate with HL Economics and HL Psychology
Freelance IT consultant for small businesses. 2020-2022
If I got your interest, or you have additional questions, don't hesitate to contact me through one of the links below!
