Why?

Build better search, ads and recommender systems that drive product goals and benefits for all parties in the ecosystem.

How?

This is a place for practitioners in search and recommender systems to come and share ideas with each other. We want to build this as a journal like NeurIPS where the best ideas are championed.

What?

Authors of this publication have built zero-to-one search and recommender systems including podcast recommendations at Google, Discord search and recommendations and FB video recommendations. They are trying to share their practical experiences and knowledge in the hopes that it is more widely useful.

Subscribe to Applied ML | Recommender systems

State of the art advances in applied machine learning with a focus on recommender systems

People

- Applied ML in Recommender systems (Discord, Google, Waymo) and High Frequency - Entrepreneur ex-(DevRev, Qplum, Tower Research, Circulum Vite).