AWS New York Summit 2018 - Threat Detection and Mitigation at Scale on AWS (SID301)
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25 дней – 5 6913:44
Опубликовано 23 июля 2018, 21:39
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Organizations are using machine learning (ML) to address a host of
business challenges, from product recommendations to demand forecasting. Until recently, developing these ML models took much time and effort, and it required expertise. In this session, we introduce Amazon SageMaker, a fully managed ML service that enables developers and data scientists to develop and deploy deep learning models quickly and easily. We walk through the features and benefits of Amazon SageMaker and discuss the uniquely designed ML algorithms that allow for optimized model training, getting you to production fast.
Organizations are using machine learning (ML) to address a host of
business challenges, from product recommendations to demand forecasting. Until recently, developing these ML models took much time and effort, and it required expertise. In this session, we introduce Amazon SageMaker, a fully managed ML service that enables developers and data scientists to develop and deploy deep learning models quickly and easily. We walk through the features and benefits of Amazon SageMaker and discuss the uniquely designed ML algorithms that allow for optimized model training, getting you to production fast.
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