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Distributed Machine Learning services and Android
Machine Learning and Artificial Intelligence represent an exciting opportunity for all of us to stop working on repetitive tasks, to improve the velocity and precision of data analysis, and to get an insight on complex and simple problems of everyday life.
How many times did you find yourself hungry around the city struggling to find a restaurant that matches your foodie preferences? How tired are you about setting your food preferences in apps that are supposed to help you when starving?
Using ML and AI, and consuming the data feed exposed on various social media, is possible to automatically generate a model to describe the food preferences of any user at any time. With such model, it is possible to provide contextual recommendations that matter to a foodie.
During this session, you will learn how to define, build, train, and deploy a machine learning model on the Amazon SageMaker infrastructure, how to feed the model with the data that come from a user social media accounts, and how to consume the SageMaker endpoints and display the food recommendations in an Android app.

Speaker: Giorgio Natili, Amazon

More online AI tech talks:

Oct 18, 2018 9:00 AM in Pacific Time (US and Canada)

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