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Building a scalable personalized recommendation system on AWS: From batch to real-time
Learn how the Everyday Essentials team built a scalable personalized recommendation platform on AWS using a batch-first architecture with Amazon MWAA for orchestration, Amazon SageMaker for training and vector search, and AWS Lake Formation for governed data access, then extended it to real-time with Amazon MemoryDB.