Explore the architectures of rotating star-planet systems in this 29-minute conference talk by Rafael Garcia, presented at the Transport in Stellar Interiors (TRANSTAR-C21) Conference. Delve into data analysis techniques, including masking, decision trees, random forests, and machine learning, applied to hot stars and exoplanets. Examine the process of pre-data conditioning and its importance in studying orbital periods and creating accurate models. Gain insights into the latest observational data and engage in a discussion on the implications for our understanding of stellar physics and planetary systems.