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Embeddings! Embeddings everywhere!

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Embeddings! Embeddings everywhere! - How to build a recommender system using representation learning.

Recommender systems are the major source of income of modern e-commerce. In this talk we will describe a large scale (over 90 millions items and 20 million registered users) e-commerce recommender system used at Allegro. The system is composed of two main parts: learning item representations and finding nearest neighbours. We will share the experience we gained from building the system.

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