Would a slot machine Data Science project be appropriate for a portfolio/LinkedIn?
Hi everyone,
I'm an upper-year undergraduate student pursuing a degree in Data Science, and I'm currently starting to build my first portfolio projects.
I've seen many beginner Data Science projects focused on relatively simple databases, SQL queries, averages, visualizations, and exploratory data analysis. I think those projects are useful for learning, but I also wanted to try building something a little more complex that would allow me to integrate several different areas.
One idea I'm interested in is building a simple slot machine from scratch, but approaching it primarily from a mathematical and data perspective.
I would start by designing the mathematical model of the machine: reels, symbols, winning combinations, probabilities, paytable, hit rate, RTP, expected value, variance, etc. Then I would program a simulation that runs a large number of spins and experimentally verify whether the observed results converge toward the theoretical values.
From those simulations, I would generate a dataset containing information about each spin or session, store the data in a SQL database, and perform queries, exploratory data analysis, and visualizations. Later, I'd also like to explore which Machine Learning applications actually make sense for this type of data—for example, anomaly detection, clustering different types of simulated sessions/behaviors, or introducing additional variables and analyzing models based on them.
My goal is for the project to demonstrate an end-to-end process: problem formulation, mathematical modeling, data generation and storage, SQL, statistical analysis, programming, and eventually Machine Learning, rather than simply working with an already prepared dataset.
My main concern is how this might be perceived in a professional portfolio.
Do you think a project involving a slot machine or gambling could be viewed negatively by recruiters or companies if I publish it on GitHub/LinkedIn, even if it is presented as a technical probability, statistics, and Data Science project?
Or, if it is properly documented and the objective is clearly explained, could it actually be an interesting project for demonstrating technical skills?
I'd also appreciate any suggestions about what you would add, remove, or change to make the project stronger from a Data Science perspective. ty