Table of Contents

Project Statement and Goals
Motivation and Background
Data Description
EDA
Data Cleaning
Metrics
Model Training
Interpreting the Model
Model Testing and Results
Literature Review

Project Statement:

Through music streaming services, many of us have access to more music than we'll ever have time to explore on our own. We build a system that can recommend new songs that will likely be compelling to a user. A playlist that the user has already created will be used as ground truth for the users taste in music.

Goals:

• Given a playlist as input, output a list of 10 tracks that will be welcomed additions to a users playlist. Users want to discover new music and conveniently add music they already love to playlists. Our system should be able to accomodate.

• Measure an R-Precision score that can give quantitative data indicating how our system compares to the state of the art and confirm that our model has successfully learned trends that generalize.

• Interpret our model to understand what features contribute to a harmonious playlist.