AWS Machine Learning Blog

Category: Artificial Intelligence

Build and visualize a real-time fraud prevention system using Amazon Fraud Detector

We’re living in a world of everything-as-an-online-service. Service providers from almost every industry are in the race to feature the best user experience for their online channels like web portals and mobile applications. This raises a new challenge. How do we stop illegal and fraudulent behaviors without impacting typical legitimate interactions? This challenge is even […]

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Take advantage of advanced deployment strategies using Amazon SageMaker deployment guardrails

Deployment guardrails in Amazon SageMaker provide a new set of deployment capabilities allowing you to implement advanced deployment strategies that minimize risk when deploying new model versions on SageMaker hosting. Depending on your use case, you can use a variety of deployment strategies to release new model versions. Each of these strategies relies on a […]

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Train graph neural nets for millions of proteins on Amazon SageMaker and Amazon DocumentDB (with MongoDB compatibility)

There are over 180,000 unique proteins with 3D structures determined, with tens of thousands new structures resolved every year. This is only a small fraction of the 200 million known proteins with distinctive sequences. Recent deep learning algorithms such as AlphaFold can accurately predict 3D structures of proteins using their sequences, which help scale the […]

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Identity verification using Amazon Rekognition

In-person user identity verification is slow to scale, costly, and high friction for users. Machine learning (ML) powered facial recognition technology can enable online user identity verification. Amazon Rekognition offers pre-trained facial recognition capabilities that you can quickly add to your user onboarding and authentication workflows to verify opted-in users’ identities online. No ML expertise […]

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Hybrid ML

Introducing hybrid machine learning

Gartner predicts that by the end of 2024, 75% of enterprises will shift from piloting to operationalizing artificial intelligence (AI), and the vast majority of workloads will end up in the cloud in the long run. For some enterprises that plan to migrate to the cloud, the complexity, magnitude, and length of migrations may be […]

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Use deep learning frameworks natively in Amazon SageMaker Processing

Until recently, customers who wanted to use a deep learning (DL) framework with Amazon SageMaker Processing faced increased complexity compared to those using scikit-learn or Apache Spark. This post shows you how SageMaker Processing has simplified running machine learning (ML) preprocessing and postprocessing tasks with popular frameworks such as PyTorch, TensorFlow, Hugging Face, MXNet, and […]

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Live call analytics for your contact center with Amazon language AI services

Update May 2022 (v0.3.0) – Architecture improvements provide simplified serverless call processing, support for additional languages, and a new deployment option to enable easy integration with Genesys Cloud contact centers using Audiohook.  See New features Your contact center connects your business to your community, enabling customers to order products, callers to request support, clients to […]

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Post call analytics for your contact center with Amazon language AI services

This blog post was last reviewed and updated March, 2022. Added support for Transcribe Call Analytics call summarization. See New features. Your contact center connects your business to your community, enabling customers to order products, callers to request support, clients to make appointments, and much more. Each conversation with a caller is an opportunity to […]

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Build custom Amazon SageMaker PyTorch models for real-time handwriting text recognition

In many industries, including financial services, banking, healthcare, legal, and real estate, automating document handling is an essential part of the business and customer service. In addition, strict compliance regulations make it necessary for businesses to handle sensitive documents, especially customer data, properly. Documents can come in a variety of formats, including digital forms or […]

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Achieve 35% faster training with Hugging Face Deep Learning Containers on Amazon SageMaker

Natural language processing (NLP) has been a hot topic in the AI field for some time. As current NLP models get larger and larger, data scientists and developers struggle to set up the infrastructure for such growth of model size. For faster training time, distributed training across multiple machines is a natural choice for developers. […]

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