Neural Collaborative Filtering
In this post well cover some of the basics of recommendation system approaches utilising neural networks.
So collaborative filtering (CF) is a recommendation generation technique that relies on user-item interactions to make predictions about what a user might like based on the historical data of user interaction with the item.
We covered collaborative filtration
using matrix factorisation is the notebook
Specifically we looked at methods such as SVD
in order to generate the user
and item
matrices, these two matrices are then multiplied together to get the corresponding scores for each user, item pairing; a model-based approach.
Neural Collaborative Filtering
(NCF) is an advanced version of model-based collaborative filtering that leverages deep learning techniques to enhance recommendation performance.