usnaveen/music-genre-classification

Contains all the notebooks of the Machine learning term project.

MUSIC GENRE CLASSIFICATION

Team Members:

• Aayush Sagar CB.EN.U4ELC20002
• Hari Varsha CB.EN.U4ELC20021
• Naveen US CB.EN.U4ELC20043

Motivation:

Machine Learning is used when it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks. Machine learning algorithms are widely used in today’s world in the various fields such as in medicine, email filtering, speech recognition, agriculture, and computer vision etc,. Data mining and Machine Learning are some of the hottest fields as the field has matured both in terms of identity and in terms of methods and tools. There is an abundance of data to learn from.

This is a term project of an University Course where we explore different machine learning algorithms using the same dataset. The dataset we chose is the GTZAN music genre classification dataset, https://www.kaggle.com/datasets/andradaolteanu/gtzan-dataset-music-genre-classification.

The first machine learning algorithm we explored using this dataset was the K-nearest neighbours algorithm for classification of data. {insert key learnings}

The second machine learning algorithm we explored using this dataset was Principal Component Analysis and the K-Means clustering of data. {insert key learnings}