Our project is centered around a clustering algorithm for songs belonging to a users playlists, wether it be 1 or 10. We will then output the recommended playlists per our clustering algorithm. We are currently thinking of implementing a K-Means clustering algorithm that allows the user to choose the number of playlists they want.

The challenges we anticipate in developing a properly functioning model are:

1. User authorization to interact with the Spotify Web API
2. Data extraction, both in gathering the data and choosing what data to use, hence point 3.
3. Feature extraction and engineering
4. Connecting a React-based frontend to a Flask API

The skills we will need to learn are:

1. Exploratory Data Analysis using Pandas, Seaborn, and Matplotlib
2. Feature Extraction to improve accuracy and reduce training time
3. Model building
4. Key Performance Indicators to measure our progress
5. Full stack web development

+-- backend -> Flask API server
| |
| +-- server.py -> server entrypoint
|
+-- frontend -> React frontend
|
+-- EDA -> initial EDA file
|
+-- Sptofy Clustering -> clustering testing/tuning

Niccolo Nobili

• Pitt CS, 2025
• [email protected]
• Check out my Personal website or LinkedIn

Amaan Kazi

• Pitt Bioengineering, 2022
• [email protected]
• Check out my LinkedIn

Pranay Jain

• Pitt Bioengineering, 2022
• [email protected]
• Check out my Personal website or LinkedIn

Adam Powley

• Pitt Computational Biology, 2024
• [email protected]