Music Genre Classification Project

Welcome to the Music Genre Classification project repository! This project aims to classify music genres using various machine learning models based on audio features extracted from .wav format files. The repository contains the code, data, and results of our efforts to accurately predict the genre of music tracks.

Tech Stack

The project is primarily developed using Python and utilizes a range of machine learning libraries and tools. Key components of our tech stack include:

• Python

• Machine Learning Libraries (scikit-learn, XGBoost, etc.)

• Audio Feature Extraction Libraries

• Jupyter Notebooks

Results

Our investigation revealed that the Support Vector Machine (SVM) and Random Forest Classifier algorithms outperformed the K-Nearest Neighbors (KNN) algorithm in music genre classification. Specifically, the Random Forest Classifier achieved the highest accuracy of 73.2%. More details about our experimentation and results can be found in the project's code and documentation.