#9: RecPack and Modularized Personalization by Froomle with Lien Michiels and Robin Verachtert

In episode nine of Recsperts we introduce RecPack which is the new recommender package for Python for easy, consistent and extensible experimentation and benchmarking. I talk to Lien Michiels and Robin Verachtert who are both industrial PhD students at the University of Antwerp. They also share how they provide modularized personalization for customers in the news and ecommerce sector at Froomle. In adition, we learn more about their research on filter bubbles as well as recommender model degradation and retraining.

Om Podcasten

Recommender Systems are the most challenging, powerful and ubiquitous area of machine learning and artificial intelligence. This podcast hosts the experts in recommender systems research and application. From understanding what users really want to driving large-scale content discovery - from delivering personalized online experiences to catering to multi-stakeholder goals. Guests from industry and academia share how they tackle these and many more challenges. With Recsperts coming from universities all around the globe or from various industries like streaming, ecommerce, news, or social media, this podcast provides depth and insights. We go far beyond your 101 on RecSys and the shallowness of another matrix factorization based rating prediction blogpost! The motto is: be relevant or become irrelevant! Expect a brand-new interview each month and follow Recsperts on your favorite podcast player.