2021-05-03, 11:00–11:25, PyData Track 1
Join this session to hear about my journey with tree-based classifiers, while tackling the problem of classifying songs into different genres. Learn how XGBoost works and what makes it so popular.
Tree-based models are some of the most common machine learning models used today. It makes sense- the basic concept is easy to grasp and easy to work with.
In this talk, we will dive into the concepts behind the names Decision Trees and XGBoost, and discuss the advantages and disadvantages in comparison to other machine learning models. On the music side, we will discover how to extract features from songs and how to use them to differentiate between genres.
This talk is intended for anyone with basic familiarity with machine learning that would like to deepen their understanding in the subjects of tree-based models, classification, and how to apply machine learning to songs.