Music Genre Classification using various Machine Learning Algorithms

Music genre classification is a complex task that involves automatically categorizing music tracks into predefined genres. Due to the subjective nature of music and the wide variety of musical elements present within each genre, this task can be challenging. However, machine learning techniques have been increasingly utilized in recent years to enhance the accuracy of music genre recommendation. Music genre classification relies on features such as melody, tempo, pitch, harmony, rhythm, and frequency to categorize music into different genres. In this paper, the GTZAN dataset is being used and to extract features, various methods such as spectrogram, and statistical analysis have been employed. We provide you with an overview of different approaches used in machine learning to achieve the highest level of accuracy using a particular algorithm, indicating it potential for use in music genre classification.