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In this demo, we show how to build a smart ad display to serve relevant advertisements in real-time, based on the inference from the audience looking at the ads. Advertising displays serve static or periodically shuffling ads, which change at regular intervals usually geared towards one segment of buyers. This results in a missed opportunity in terms of catering to other segments who would be near a billboard or a display. Learn how to build an intelligent solution where an advertising display uses an on-device camera, or feeds from nearby CCTV cameras of people passing by, to identify the audience and serving them personalized advertisements in near real time. We also cover how Amazon SageMaker and Amazon Rekognition can extract attributes like age, gender, height, face-positioning and use these attributes with Amazon Personalize to serve more relevant and targeted advertisements.

Amazon Personalize enables developers to build applications with the same machine learning (ML) technology used by Amazon.com for real-time personalized recommendations – no ML expertise required.

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.

Amazon SageMaker is a cloud machine-learning platform that was launched in November 2017. SageMaker enables developers to create, train, and deploy machine-learning models in the cloud. SageMaker also enables developers to deploy ML models on embedded systems and edge-devices.

Amazon Rekognition provides fast and accurate face search, allowing you to identify a person in a photo or video using your private repository of face images. You can also verify identity by analyzing a face image against images you have stored for comparison.

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