Abstract for Music Genres Classification using K-Nearest Neighbors (KNN) in Python:
This project introduces a Music Genres Classification System implemented in Python, employing the K-Nearest Neighbors (KNN) algorithm. The goal is to develop an efficient and accurate method for automatically classifying music into predefined genres. The system utilizes audio features, such as spectral characteristics and rhythm patterns, extracted from music samples. The KNN algorithm is employed to classify unknown music tracks based on their similarity to labeled samples in the feature space. The project aims to contribute to the field of music information retrieval, providing a valuable tool for organizing and categorizing large music databases. The use of Python and the KNN algorithm ensures a practical and accessible solution for music genres classification, with potential applications in music recommendation systems and content organization.