Join us live with Fast Forward Labs to discuss the recently possible in Machine Learning and AI. Being able to recommend an item of interest to a user (based on their past preferences) is a highly relevant problem in practice. A key trend over the past few years has been session-based recommendation algorithms that provide recommendations solely based on a user’s interactions in an ongoing session, and which do not require the existence of user profiles or their entire historical preferences. This report explores a simple, yet powerful, NLP-based approach (word2vec) to recommend a next item to a user. While NLP-based approaches are generally employed for linguistic tasks, here we exploit them to learn the structure induced by a user’s behavior or an item’s nature.

Kafka Summit Europe 2021 takes places May 11-12, what will be the major takeaways and interesting points from the event? Join us, live, to discuss what we think are the most important things to know. Take advantage of live Q&A with some of Cloudera's event streaming experts.