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As the ability to deliver more sophisticated digital experiences evolve over time, the expectation and demand from customers to receive a more personalized experience from companies and products they engage with have also increased. Customers today expect real-time, curated experiences across digital channels as they consider, purchase, and use products and services. 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. Learn how to build applications capable of delivering a wide array of personalized experiences, including specific product recommendations, personalized product re-ranking, and customized direct marketing – with no ML experience required.

Amazon Personalize makes it easy for developers to use machine learning (ML) to build applications capable of delivering a wide array of personalized experiences, including specific product recommendations, personalized product re-ranking, and customized direct marketing-with no ML experience required.

Learn more about Amazon Personalize at – https://amzn.to/3lU6G1p

Amazon Personalize makes it easy for developers to build applications capable of delivering a wide array of personalization experiences, including specific product recommendations, personalized product re-ranking, and customized direct marketing. Amazon Personalize is a fully managed machine learning service that goes beyond rigid static rule based recommendation systems and trains, tunes, and deploys custom ML models to deliver highly customized recommendations to customers across industries such as retail and media and entertainment.

Amazon Personalize provisions the necessary infrastructure and manages the entire ML pipeline, including processing the data, identifying features, using the best algorithms, and training, optimizing, and hosting the models. You will receive results via an Application Programming Interface (API) and only pay for what you use, with no minimum fees or upfront commitments. All data is encrypted to be private and secure, and is only used to create recommendations for your users.

#AWS​ #MachineLearning​


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