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A simple web application that classifies a song's genre using a CNN model. It also includes the data collection process, as well as how the CNN model was developed.

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Music Genre Classifier

This repository demonstrates how you can create a CNN to classify a song's genre, and deploy the model into a Heroku web application.

There are three branches associated to this repository:

  • master - contains documentation on how the convolutional neural network model was created using Keras with Tensorflow as a backend framework. It also includes python code on how the music data was collected and formatted prior to the training process of the neural network.

  • streamlit-app-v1.0 - contains the necessary code to deploy the web application into Heroku, and includes instruction how to deploy the web application to Heroku.

  • command-line-interface-v1.0 - contains the minimal amount of code for running the app via the terminal.

Note: master and streamlit branch can run the streamlit app locally. Simply run the command streamlit run app.py. To run some tests before running the application locally, or deploying the model into Heroku, run the tests.py file and see if there are any errors. For the link to the app see https://music-genre-classifier-app.herokuapp.com

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A simple web application that classifies a song's genre using a CNN model. It also includes the data collection process, as well as how the CNN model was developed.

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