Innovative Recommendation Applications Using Two Tower Embeddings at Uber

Learn how we developed a unified, global, Two-Tower Embedding model to replace 1,035 city-specific DeepMF models, decreasing training time by orders of magnitude and working at Uber scale with millions of eaters and stores and hundreds of millions of items

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