11
Apr
This tutorial will walk you through using PyTorch to implement a Neural Collaborative Filtering (NCF) recommendation system. NCF extends traditional matrix factorisation by using neural networks to model complex user-item interactions. Introduction Neural Collaborative Filtering (NCF) is a state-of-the-art approach for building recommendation systems. Unlike traditional collaborative filtering methods that rely on linear models, NCF utilizes deep learning to capture non-linear relationships between users and items. In this tutorial, we’ll: Prepare and explore the MovieLens dataset Implement the NCF model architecture Train the model Evaluate its performance Generate recommendations for users Setup and Environment First, let’s install the necessary libraries…
