You see all these websites with recommendations for things to buy or watch. During this talk Jettro walks you through all the steps to create yourself a recommender. Getting data for your recommendations from user events. Handling and enriching these user events before storing them ready to be used by the recommender. Creating a recommendation using concepts like (non) personalised recommendations, cold users, cold products and similarity algorithms L1/L2-Norm, Cosine, Pearson, k-means clustering. After this presentation you know what you need to do to get recommendations on your website.
Fellow - Luminis
Software Developer / Architect with a lot of hands on experience in Java, AngularJS, Elasticsearch and lots of others tools. He has a great experience with importing and transforming data as well as presenting and visualising the data.