About this document
MovieLens 100K User-Based Recommender by caixuanhoa2004 is a document available to read on EtoBox.
The document outlines a two-part process for building a movie recommendation system using the MovieLens 100K dataset. Part 1 involves downloading the dataset, loading ratings data, splitting it into training and testing sets, and displaying basic statistics. Part 2 focuses on implementing user-based collaborative filtering by calculating user similarity, identifying similar users, predicting ratings, and recommending movies.
- Author
- caixuanhoa2004
- Language
- EN