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Product Enrichment and Recommender Systems

Posted Aug 04, 2022 | Views 680
# eezylife Inc
# Product Enrichment
# Recommender Systems
# eezy.ai
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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.

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Amr Mashlah
Head of Data Science @ eezylife Inc.

Amr is the head of data science at eezy, where he leads the development of their recommender engine. Amr has a master's degree in AI and has been working with startups for 6 years now.

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Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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Skylar Payne
Machine Learning Engineer @ HealthRhythms

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!

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SUMMARY

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.

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