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
Conclusion and What’s Next
Literature Review

Literature Review

We considered the following papers in our research and brainstorming:

• Evaluation in Information Retrieval
• A Review on Evaluation Metrics for Data Classification Evaluations
• Current Challenges and Visions in Music Recommender Systems Research
• Natural Language Processing in Information Retrieval

These papers elucidate ideas in information retreival, natural language processing and metrics. “Current Challenges and Visions” made of more aware of the academic state of recommendation systems for music. It also prompted us to think about how other dimensions of data, like emotion and context will come to play a role in the future.

The following youtube video was insightful in that it presents ideas that workers at Spotify are already putting into practice:

Machine Learning & Big Data for Music Discovery presented by Spotify