Identifying what genre a particular song belongs to has been a cakewalk for humans. Can we train the machines to do this job for us? With this motivation in mind, we used Machine Learning as a tool for implementing this task of genre identification. In this project, we have explored methods for exploratory data analysis, feature selection, hyperparameter optimization, and eventual implementation of several algorithms for classification.
For more information, you can refer to the report over here. A brief presentation describing our project can be found over here.
The complete implementation of our code can be found over here.
These were the classification results on the Million Song Genre Dataset, made available by LabROSA at Columbia University. The model used is a Random forest using hyperparameters obtained from Bayesian optimization.