Recommendation Engine for IBM Watson This project is a part of Udacity and IBM Watson collaboration
In this project I am creating a recommendation system for the IBM Watson community. The recommendation system suggests articles for users to read.
The recommender system can make recommendations in a number of ways:
Collaborative Filtering - uses similarity of users and recommends the most popular articles read by similar users
Rank Based Recommendations - recommends the highest ranked articles starting with the most highly ranked
Content Based Filtering - produces recommendations based on similarity of articles' titles to one another. Uses Natural Language Processing (NLP) methodology to analyse and rank articles by similarity. SVD - Matrix Factorization Recommendations - uses matrix operations to predict the ranking