Coffee Sessions #114

Product Enrichment and Recommender Systems

The difficulties of making multi-modal recommender systems. How it can be easy to know something about a user but very hard to know the same thing about a product and vice versa? For example, you can clearly know that a user wants an intellectual movie, but it is hard to accurately classify a movie as intellectual and fully automated.

In this episode

Marc Lindner

Marc Lindner

Co-Founder COO, eezylife Inc.

Marc has a background in Knowledge Engineering. He's Always extremely product-focused with anything to do with Machine Learning. Marc built several products working together with companies such as Lithium Technologies etc. and then co-Founded eezy.

Twitter

LinkedIn

Amr Mashlah

Amr Mashlah

Head of Data Science, eezylife

Marc has a background in Knowledge Engineering. He's Always extremely product-focused with anything to do with Machine Learning. Marc built several products working together with companies such as Lithium Technologies etc. and then co-Founded eezy.

Twitter

LinkedIn

Demetrios Brinkmann

Demetrios Brinkmann

Host

Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.

Skylar Payne

Skylar Payne

Host

Data is a superpower, and Skylar has been passionate about applying it to solve important problems across society. For several years, Skylar worked on large-scale, personalized search and recommendation at LinkedIn -- leading teams to make step-function improvements in our machine learning systems to help people find the best-fit role. Since then, he shifted my focus to applying machine learning to mental health care to ensure the best access and quality for all. To decompress from his workaholism, Skylar loves lifting weights, writing music, and hanging out at the beach!