This article presents the activities carried out in the compulsory stage
for the completion of the Technical Course in Integrated Computing IFRS -
Campus Ibirubá . These are focused on software development area, with a brief
involvement in the hardware area.
In this work, we attempt to solve the Hit Song Science problem, which aims to predict which songs will become chart-topping hits. We constructed a dataset with approximately 1.8 million hit and non-hit songs and extracted their audio features using the Spotify Web API. We test four models on our dataset. Our best model was random forest, which was able to predict Billboard song success with 88% accuracy.