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Personalizing the user experience is proven to increase discoverability, user engagement and satisfaction, and revenue; however, many AWS customers find personalization hard to get right. Effective recommender systems require solving multiple hard problems, including constantly changing user behavior, new catalog items (cold start), etc. In this session, we cover some of the most common methods of personalization/recommendation. Also, Amazon Prime Video shares the evolution of its recommendation system and the real-world challenges it faced when building recommendation systems at scale.

Recommendation engines make targeted marketing campaigns, re-ranking of items, personalized notifications, and personalized search possible. In this session, we deep-dive into using Amazon Personalize to create and manage personalized recommendations efficiently, letting you focus on the real value of the data for your business. We discover how these deep learning techniques have a direct impact on the bottom line of your business by increasing engagement, click-through, satisfaction, and revenue. Learn from customer examples and dive into some live demonstrations.

Learn more about Amazon Personalize at – https://amzn.to/39WpjyD

#AWS​ #MachineLearning​


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