An archive of early hands-on practice — case studies, experiments, and exploratory notebooks from when I was building my data analysis foundations.
These are intentionally rough: they're where I learned by doing, before moving on to more structured, end-to-end work. Kept public as an honest record of the journey.
👉 For polished, end-to-end work, see my portfolio and pinned repositories.
| Notebook / file | What it explores |
|---|---|
KALBE_Case_Study(fail).ipynb |
A business case study attempt — kept "fail" and all, because the debugging is where the learning happened. |
KALBE_Regression_Test.ipynb |
Practicing regression modelling and evaluation. |
Tritronik_01.ipynb |
Exploratory data analysis on a sample dataset. |
testETL001.ipynb |
An early ETL / data-pipeline experiment. |
dataAnalysis001.pdf |
Notes / output from an early analysis exercise. |
Python · pandas · Jupyter / Google Colab · scikit-learn
These are practice projects. They're not representative of my current standard of work — that lives in my main portfolio.