π Dev.to
The Work Behind βRecommended for Youβ
My journey into recommendation systems started with curiosity: how do large companies decide what to recommend to each user? While exploring their approaches, I wanted to understand how similar ideas could be applied to associations and their members.
Exploring the approaches
I started by learning about the different ways recommendations can be generated:
Content-based filtering : Suggest items based on their similarity to a personβs interests or previous choices.
Coll...

