Following my Capstone, I wanted to see if I could host my song lyric generator as a web application. There are tons of tutorials out there; unfortunately, few of them touch on hosting large models (like the LSTM model I developed for my project) and running them on the servers directly supported by sites likeContinue reading “Designing Python Web Applications”
Tag Archives: Python
Capstone Project: Lyric Generation
This May, I concluded my M.S. in Data Science Program and my Capstone project on song lyric generation. While I doubt any of them are going to be hits (most of the generated songs still require a bit of editing, and saying that there’s evidence of a narrative is a stretch), it taught me aContinue reading “Capstone Project: Lyric Generation”
Spotify Time Series Analysis Pt. 2
This is a continuation from my previous post, Spotify Time Series Analysis Pt. 1. While not required reading, it might provide some context for what I’m discussing here! A Deep Dive into Genres and Artists How do by artist/genre listening habits change over time? How are different artists and genres related in my listening history?Continue reading “Spotify Time Series Analysis Pt. 2”
Spotify Daily Mix Analysis
I recently got back into analyzing my Spotify data and wanted to compare my listening habits to the general population’s. Additionally, while I could probably have a greater diversity in musical taste, I was curious to see how traits of the music I listened to varied across different segments of what I listen to. EveryContinue reading “Spotify Daily Mix Analysis”
Adventures in Spotipy
Isn’t it a bummer that Spotify’s Wrapped only comes once a year? Well, turns out they offer something that is nearly as good; Spotify Web API Endpoints. You can get basic information like track name, artist name and track popularity, as well as somewhat more obscure information found in “audio analysis.” For my forthcoming analysis,Continue reading “Adventures in Spotipy”
Ange Olson 