musical snobbery, with a touch of machine learning
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Updated
Jul 25, 2016 - Python
musical snobbery, with a touch of machine learning
A machine learning approach to classify songs by mood.
This app simulates a music tracker system on a client-server architecture
Song Popularity Predictor
Based on the idea of Spotify : a concrete example to understand how graph databases work with Neo4j. The challenge is to create a music recommendation algorithm using a very large database of songs (Million Song Challenge Dataset) with an API to interact with (Symfony).
Song lyrics generation using Recurrent Neural Networks (RNNs)
Data Modeling with Postgres
Data Engineering Projects: SQL, NoSQL, Data Warehousing, Date Lake & Data Pipeline
ETL Pipeline from AWS S3 to Redshift
Recommending great songs to users based on their listening history!
Final Project for STA 141C with Dr. Bo Yu-Chien Ning
Analysis of new songs website data using Postgres SQL Functions to extract insights, business improvement, and understanding the relations between features.
This is a dataset consisting of all song lyric words found on all of Taylor Swift's studio albums (up to and including TTPD), as well as a selection of other songs written by her.
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