Thanks for stopping by! I’m a data science enthusiast based in Wrocław, Poland, with a strong foundation in mathematics and a passion for turning theory into something that actually works (and doesn't crash at 00:00 a.m. :D).
I’m fascinated by how data, combined with solid statistical thinking and well-designed algorithms, can reveal patterns and solve real problems. Whether it’s forecasting, optimization, or classification, I like getting my hands dirty with the math and code behind the models — not just using them, but understanding how they work.
My go-to language is Python, and I often build things from scratch to really grasp the mechanics. Alongside that, I work with a mix of libraries and tools depending on the task:
- NumPy — for numerical work and linear algebra
- Polars & Pandas — for fast and flexible data wrangling
- Scikit-learn — as a reference for model design, though I often reimplement algorithms myself
- Seaborn & Matplotlib — for nice visualizations (I don't like raw numbers, prefer beautiful charts)
- Jupyter Notebooks & Quarto — for exploration and reproducible analysis
- SQL — for querying and managing data
- Excel — for quick prototyping and sharing results
- Power BI — for dashboards and KPIs that are really aesthetic (better than seaborn I dare say)
- Databricks — for large-scale data preprocessing with cloud and AI tools
- R — for statistical analysis and visualization
I’m always looking to level up. Right now, I’m:
- Getting into Databricks for large-scale data preprocessing with cloud and AI tools
- Keeping an eye on Mojo for its potential in high-performance data workflows
📞 Feel free to connect as I explore new machine learning techniques, statistical approaches, and data visualization tools! Find me on LinkedIn or email me at pawel.tomasz.nowak04@gmail.com.