AWS Architecture Blog

Category: Amazon SageMaker

architecture for the solution

Real-Time In-Stream Inference with AWS Kinesis, SageMaker & Apache Flink

As businesses race to digitally transform, the challenge is to cope with the amount of data, and the value of that data diminishes over time. The challenge is to analyze, learn, and infer from real-time data to predict future states, as well as to detect anomalies and get accurate results. In this blog post, we’ll […]

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Field Notes: Inference C++ Models Using SageMaker Processing

Machine learning has existed for decades. Before the prevalence of doing machine learning with Python, many other languages such as Java, and C++ were used to build models. Refactoring legacy models in C++ or Java could be forbiddingly expensive and time consuming. Customers need to know how they can bring their legacy models in C++ […]

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Machine learning solution developed for customer

Building a Self-Service, Secure, & Continually Compliant Environment on AWS

Introduction If you’re an enterprise organization, especially in a highly regulated sector, you understand the struggle to innovate and drive change while maintaining your security and compliance posture. In particular, your banking customers’ expectations and needs are changing, and there is a broad move away from traditional branch and ATM-based services towards digital engagement. With […]

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Pre-processing pipeline architecture

Building a Scalable Document Pre-Processing Pipeline

In a recent customer engagement, Quantiphi, Inc., a member of the Amazon Web Services Partner Network, built a solution capable of pre-processing tens of millions of PDF documents before sending them for inference by a machine learning (ML) model. While the customer’s use case—and hence the ML model—was very specific to their needs, the pipeline that does […]

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Formula 1 logo - 2020

Formula 1: Using Amazon SageMaker to Deliver Real-Time Insights to Fans

The Formula One Group (F1) is responsible for the promotion of the FIA Formula One World Championship, a series of auto racing events in 21 countries where professional drivers race single-seat cars on custom tracks or through city courses in pursuit of the World Championship title. Formula 1 works with AWS to enhance its race […]

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TMA LIVE

Binge-Watch Live This is My Architecture Videos from AWS re:Invent

AWS re:Invent 2019 was a whirlwind of activity, especially in the Expo Hall, where the AWS team spent four days filming 12 live This is My Architecture videos for Twitch. Watch one a day for the next two weeks…or eat them all in one sitting. Whichever you do, you’re guaranteed to learn something new. Accolade […]

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FogHorn

FogHorn: Edge-to-Edge Communication and Deep Learning

FogHorn is an intelligent Internet of Things ( IoT) edge solution that delivers data processing and real-time inference where data is created. As “the only ‘real’ edge intelligence solution in the market today,” FogHorn is powered by a hyper-efficient Complex Event Processor (CEP) and delivers comprehensive data enrichment and real-time analytics on high volumes, varieties, […]

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Architecture Monthly - July 2019

Architecture Monthly Magazine for July: Machine Learning

Every month, AWS publishes the AWS Architecture Monthly Magazine (available for free on Kindle and Flipboard) that curates some of the best technical and video content from around AWS. In the June edition, we offered several pieces of content related to Internet of Things (IoT). This month we’re talking about artificial intelligence (AI), namely machine […]

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Store, Protect, Optimize Your Healthcare Data with AWS: Part 2

Leveraging Analytics and Machine Learning Tools for Readmissions Prediction This blog post was co-authored by Ujjwal Ratan, a senior AI/ML solutions architect on the global life sciences team. In Part 1, we looked at various options to ingest and store sensitive healthcare data using AWS. The post described our shared responsibility model and provided a […]

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