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# System prepended metadata

title: 'Meeting #4 (13/01/2022)—Individual Discussion'

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# 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 