Nicolette Peterkin

Nicolette's thirteen repositories read as a structured data-science bootcamp in progress — week-numbered Jupyter and Python work on cross-selling for a credit union, business-understanding write-ups, and a Heroku/Flask deployment exercise. The focus is unambiguously data and ML (80% of her discipline mix), with evidence of the full project lifecycle from intake reports to a cloud deploy. As expected at this stage, there are no stars, no commits in the last year, and the coursework is abandoned post-completion. An early data/ML practitioner with a clear learning trajectory and not yet an independent body of work.