Extracted features and classified GTZAN Dataset via deep neural networks with reduced number of parameters and achieved a maximum of 81.62% classification accuracy using 1D-CNN.

With day-by-day increasing internet penetration, huge amount of useful data is available at proximity to people. Although it seems that there is ease of access to data, but this exponentially increasing amount of data brings to table a new problem – most of this chunk is unclassified. Through this project, we aim to resolve this problem with som…

This repository contains the code for some models that classify music files into their specific genres