This project is an Agent-Based Model (ABM) implemented using the Python-based Mesa library. The model is inspired by the seminal work "Growing Artificial Societies" by Joshua M. Epstein and Robert Axtell, which introduces the Sugar and Spice Model, a framework for exploring economic, social, and ecological dynamics in artificial societies.
YouTube Download & Source Separation
This project demonstrates the use of Apache Airflow to orchestrate a multi-step pipeline for downloading a song from YouTube and performing source separation using the Librosa library.
YouTube Quota Calculator
I frequently work with the YouTube API, which inspired me to create the YouTube Quota Calculator and Logger. This tool tracks and logs my API usage, including the specific functions called and the quota consumed, ensuring I stay within my daily limit. By providing real-time insights into usage patterns, the tool helps me optimize API calls and manage resources efficiently. It's a practical solution for maintaining control over quota limits while maximizing productivity with the YouTube API.
Clustering By Vocal Features
This project builds on the yt_download_and_source_separation project by using the extracted foreground vocals for feature analysis and clustering. It extracts multiple features from each vocal file to group similar audio characteristics. The primary goal is to distinguish artists based on their vocal traits and, ultimately, to identify artists with similar vocal sounds for recommendation purposes.
