The Machine Learning Based Music Genre Classification on Spotify Data project aims to predict music genres using machine learning algorithms trained on Spotify data. By leveraging the vast amount of information available in the audio features of songs, the project seeks to automatically classify songs into different genres based on their characteristics.
Here's the link to the dataset. The above Spotify dataset has 42,305 instances and 22 features.
After training and evaluating the machine learning models on the Spotify dataset, the project achieved an accuracy of 78% using the Bagging Classifier algorithm for music genre classification. This accuracy score indicates the percentage of correctly predicted genres for the given songs.
Here's the link to demo of the project.