Build a system for catching adverse events in real-time using Amazon SageMaker and Amazon QuickSight

Favorite Social media platforms provide a channel of communication for consumers to talk about various products, including the medications they take. For pharmaceutical companies, monitoring and effectively tracking product performance provides customer feedback about the product, which is vital to maintaining and improving patient safety. However, when an unexpected medical

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Shared by AWS Machine Learning October 5, 2021

Detect defects in automotive parts with Amazon Lookout for Vision and Amazon SageMaker

Favorite According to a recent study, defective products cost industries over $2 billion from 2012–2017. Defect detection within manufacturing is an important business use case, especially in high-value product industries like the automotive industry. This allows for early diagnosis of anomalies to improve production line efficacy and product quality, and

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Shared by AWS Machine Learning October 5, 2021

Serve 3,000 deep learning models on Amazon EKS with AWS Inferentia for under $50 an hour

Favorite More customers are finding the need to build larger, scalable, and more cost-effective machine learning (ML) inference pipelines in the cloud. Outside of these base prerequisites, the requirements of ML inference pipelines in production vary based on the business use case. A typical inference architecture for applications like recommendation

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Shared by AWS Machine Learning September 30, 2021

Deploy multiple machine learning models for inference on AWS Lambda and Amazon EFS

Favorite You can deploy machine learning (ML) models for real-time inference with large libraries or pre-trained models. Common use cases include sentiment analysis, image classification, and search applications. These ML jobs typically vary in duration and require instant scaling to meet peak demand. You want to process latency-sensitive inference requests

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Shared by AWS Machine Learning September 29, 2021

Virtu Financial enables its customers to apply advanced analytics and machine learning on trade and market data by provisioning Amazon SageMaker

Favorite This is a guest post by Erin Stanton, who currently runs the Global Client Support organization for Virtu Analytics.  Virtu Financial is a leading provider of financial services and products that uses cutting-edge technology to deliver liquidity to the global markets and innovative, transparent trading solutions to its clients.

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Shared by AWS Machine Learning September 29, 2021