The GitHub respository for the Data Divers: Music Recommendation App capstone project

Tech Lead: Andrew Mark Dale || 100491442
Team Member: Abednego Ndegwa || 100941581
Team Member: Ashutosh Pandey || 100941194
Team Member: Darren Saguil || 100458141
Team Member: Nikhil Lohar || 100925168

Reasoning: Portmanteau of Recommendation + Nearest Neighbours and a play on reckoning. Since we're calculating or estimating recommendations for a particular song, we feel this is perfect.

Most of the work has been done without constantly uploading to GitHub. We will correct this for future portions of the project.

Uploaded documents: Kick-Off Meeting PowerPoint, MVP PowerPoint, MMP PowerPoint, Final Presentation PowerPoint

When testing our application, please use the following login credentials. Spotify requires that applications be approved by their team to allow for any user to use the system. Therefore, this is the login credentials approved for our application currently.

Link : RecNN.app

Email : aidi10032023@gmail.com

Password : aidi2023

We have included screenshots below for the final phase of the project.

You can also run the project locally if you wish:

Get the code by either cloning this repository using git

git clone https://github.com/TLAndrewMarkDale/DataDivers_MusicRecommendationApp.git

... or downloading source code as a zip archive

You will need Node.js version 18.0 or greater installed on your system.

Once downloaded, open the terminal in the project directory and navigate to music-recommendation-frontend , and install dependencies with:

npm install

After all the dependencies is being installed. Then start the frontend app with:

npm run dev

This hosts the front-end on http://localhost:3000/.

Login Page

Spotify Login Page

Spotify Grant Access Page

Home Page

Song Recommendation Page

Song Added to Playlist Page

Playlist Created Successfully

Playlist in the Spotify Client

Login Page

Spotify Login Page

Spotify Grant Access Page

Home Page

Song Recommendation Page

Song Added to Playlist Page

Clicked on Create Playlist Button

Playlist Created Successfully

Playlist in the Spotify Client

Home page

Home with search result

Recommendation page

You will need Python version 3.10.12 or greater installed on your system

Once downloaded, open the terminal in the project directory and navigate to music-recommendation-backend , and install dependencies with:

pip install flask
pip install numpy
pip install flask-cors
pip install scikit-learn
pip install sklearn

After all the dependencies is being installed. Then start the backend app with:

python flask_NN.py

This hosts the python back-end on http://localhost:5000

Now that the server is running, feel free to use the demo or the locally built project!