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Live Meeting Assistant with Amazon Transcribe, Amazon Bedrock, and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

It’s straightforward to deploy in your AWS account. Prerequisites You need to have an AWS account and an AWS Identity and Access Management (IAM) role and user with permissions to create and manage the necessary resources and components for this application. Everything you need is provided as open source in our GitHub repo.

APIs 106
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Knowledge Bases for Amazon Bedrock now supports hybrid search

AWS Machine Learning

Use hybrid search and semantic search options via SDK When you call the Retrieve API, Knowledge Bases for Amazon Bedrock selects the right search strategy for you to give you most relevant results. You have the option to override it to use either hybrid or semantic search in the API.

APIs 106
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Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions

AWS Machine Learning

The solution uses the following services: Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale. Amazon Rekognition offers pre-trained and customizable computer vision (CV) capabilities to extract information and insights from your images and videos.

APIs 92
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Best practices for building secure applications with Amazon Transcribe

AWS Machine Learning

Amazon Transcribe can be used for transcription of customer care calls, multiparty conference calls, and voicemail messages, as well as subtitle generation for recorded and live videos, to name just a few examples. Applications must have valid credentials to sign API requests to AWS services.

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The 5 Best Genesys Alternatives for Your Business

aircall

Its features include AI, voice, analytics, and workforce management. The best integrations should include a one-click set-up, webhooks and API, computer telephony integration (CTI), contact synchronization, and insight cards. Analytics When it comes to the success of a cloud-based phone system , success is in the details.

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Build and train ML models using a data mesh architecture on AWS: Part 1

AWS Machine Learning

Large enterprises sometimes set up a center of excellence (CoE) to tackle the needs of different lines of business (LoBs) with innovative analytics and ML projects. To generate high-quality and performant ML models at scale, they need to do the following: Provide an easy way to access relevant data to their analytics and ML CoE.

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Run an audience overlap analysis in AWS Clean Rooms

AWS Machine Learning

The following are key concepts and prerequisites to use AWS Clean Rooms: Each party in the analysis (collaboration member) needs to have an AWS account. The collaboration creator uses the invitee’s AWS account ID as input to send invitations. Prerequisites To invite another person to a collaboration, you need their AWS account ID.