In the second but last module, I look into the other popular recommendation approach: content-based filtering, extending it to a hybrid recommender later on. Here, I use the MatchBox recommender provided in AzureML.
[00:48] Content-based filtering
[04:10] Demo: MatchBox recommender - training the content-based filtering model
[11:56] Demo: MatchBox recommender - deploying the content-based filtering model as a web service
[16:07] Demo: MatchBox recommender - extend to hybrid approach (training)
[27:27] Demo: MatchBox recommender - deploy the hybrid recommender as a web service
[31:45] Wrapping up.
The accompanying step-by-step guide can be found in the GitHub repository Recommenders in Azure.
This Channel9 video is part of a free online course on Microsoft Virtual Academy: Building Recommendation Systems in Microsoft Azure.