# Meeting #4 (13/01/2022)—Individual Discussion
11:00-13:00, Online via MS Teams

## Tridham - Machine Learning for a Music Recommendation System
• Focus a bit more on matrix factorisation application by researching theory
• Research on matrix factorisation theory and how it can be used for project
• Selecting latent components for matrix factorisation
• Ways to determine K for dimensionality reduction
• Research more on TF-IDF and what each component in the formula represents
• Possible integration of Matrix factorisation and TF-IDF methods (hybrid recommender)
• Improving presentation for final report by centring formulas etc
• After that can do data exploration and begin coding
• Presenting research on matrix factorisation to group in early semester 2
• Discussed timeslots for future group meetings

## Yuhao

## Quentin