1 時間
AIM204: Smarter Event-Driven Edge with Amazon SageMaker & Project Flogo AWS re:Invent 2018
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- テクノロジー
A single device can produce thousands of events every second. In traditional implementations, all data is transmitted back to a server or gateway for scoring by a machine learning (ML) model. This data is also stored in a data repository for later use by data scientists. In this session, we explore data science techniques for dealing with time series data leveraging Amazon SageMaker. We also look at modeling applications using deterministic rules with streaming pipelines for data prep, and model inferencing using deep learning frameworks directly onto edge devices or onto AWS Lambda using Project Flogo, an open-source event-driven framework. This session is brought to you by AWS partner, TIBCO Software Inc.
A single device can produce thousands of events every second. In traditional implementations, all data is transmitted back to a server or gateway for scoring by a machine learning (ML) model. This data is also stored in a data repository for later use by data scientists. In this session, we explore data science techniques for dealing with time series data leveraging Amazon SageMaker. We also look at modeling applications using deterministic rules with streaming pipelines for data prep, and model inferencing using deep learning frameworks directly onto edge devices or onto AWS Lambda using Project Flogo, an open-source event-driven framework. This session is brought to you by AWS partner, TIBCO Software Inc.
1 時間