Collaborative Filtering and Embeddings — Part 1
Recommendation systems are all around us. From Netflix to Amazon to even Medium, everyone is trying to understand our taste so that they can drive us into continuous engagement. You’ll be amazed by the amount of work that goes behind this. Let’s try to understand the mechanics of one such way of developing recommendation systems.
Introduction
In this series of articles I’ll explain collaborative filtering, a very common technique for developing automated recommendation systems (although the use case is not limited to recommendations). However, what makes this discussion interesting is how we can understand a more general concept of embeddings while implementing this technique. If you haven’t heard about this term no need to worry, you’ll have a good idea by the end of this post.
Part 1:
- Basic idea behind collaborative filtering
- A simple algorithm to implement collaborative filtering in excel (yeah you read it right!!)
- Understanding the concept of embeddings and bias
Part 2:
- Implementation of collaborative filtering using fastai library
- Interpreting and visualising embeddings