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Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning Blog

In this post, we discuss how the AWS AI/ML team collaborated with the Merck Human Health IT MLOps team to build a solution that uses an automated workflow for ML model approval and promotion with human intervention in the middle. A model developer typically starts to work in an individual ML development environment within Amazon SageMaker.

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Moderate your Amazon IVS live stream using Amazon Rekognition

AWS Machine Learning Blog

You can deploy this solution to your AWS account using the AWS Cloud Development Kit (AWS CDK) package available in our GitHub repo. Using the AWS Management Console , you can create a recording configuration and link it to an Amazon IVS channel. In this section, we briefly introduce the system architecture.

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Accelerate machine learning time to value with Amazon SageMaker JumpStart and PwC’s MLOps accelerator

AWS Machine Learning Blog

In this post, we start with an overview of MLOps and its benefits, describe a solution to simplify its implementations, and provide details on the architecture. We finish with a case study highlighting the benefits realize by a large AWS and PwC customer who implemented this solution. The following diagram illustrates the workflow.

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Reduce call hold time and improve customer experience with self-service virtual agents using Amazon Connect and Amazon Lex

AWS Machine Learning Blog

Solution overview To tackle these challenges, the KYTC team reviewed several contact center solutions and collaborated with the AWS ProServe team to implement a cloud-based contact center and a virtual agent named Max. Amazon Lex and the AWS QnABot Amazon Lex is an AWS service for creating conversational interfaces.

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Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

AWS Machine Learning Blog

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. Applied AI Specialist Architect at AWS. For more information, see Amazon SageMaker geospatial capabilities.

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This AI newsletter is all you need (#36)

Towards AI

The strategic partnership between Hugging Face and Amazon Web Services (AWS) looks like a positive step in this direction and should increase the availability of open-source data sets and models hosted on Hugging Face. We were also pleased to see the release of Meta’s LLaMA, 4 foundation models ranging from 7B to 65B parameters.

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Threads Dev Interview 7: @tomjohnson3

Data Science 101

We’re just big fans of effortless team collaboration It’s a dev tool designed to enhance distributed software development by providing a collaborative and visual tool for managing complex system architectures. About 10 years ago I began thinking about a platform like this to make working on distributed software easier.