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Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

AWS Machine Learning

These customers need to balance governance, security, and compliance against the need for machine learning (ML) teams to quickly access their data science environments in a secure manner. We also introduce a logical construct of a shared services account that plays a key role in governance, administration, and orchestration.

APIs 68
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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

MLOps – Model monitoring and ongoing governance wasn’t tightly integrated and automated with the ML models. Reusability – Without reusable MLOps frameworks, each model must be developed and governed separately, which adds to the overall effort and delays model operationalization.

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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.

APIs 106
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Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

AWS Machine Learning

Applications and services can call the deployed endpoint directly or through a deployed serverless Amazon API Gateway architecture. To learn more about real-time endpoint architectural best practices, refer to Creating a machine learning-powered REST API with Amazon API Gateway mapping templates and Amazon SageMaker.

Scripts 90
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How Earth.com and Provectus implemented their MLOps Infrastructure with Amazon SageMaker

AWS Machine Learning

Machine Learning Operations (MLOps) provides the technical solution to this issue, assisting organizations in managing, monitoring, deploying, and governing their models on a centralized platform. That is where Provectus , an AWS Premier Consulting Partner with competencies in Machine Learning, Data & Analytics, and DevOps, stepped in.

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The Future of Debt Collection Agencies: Contact Center Technology and Customer-Centric Strategies

NobelBiz

this is governed by the Fair Debt Collection Practices Act (FDCPA), which sets guidelines on how collectors can conduct themselves, the times and methods by which they can contact debtors, and the actions they are prohibited from taking. In the U.S.,

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How to Successfully Implement Customer Journey Analytics – Part 1

Pointillist

Estimate project duration by speaking with the vendors you have shortlisted and any industry consultants/analysts who may be advising you. Pointillist can handle data in all forms, whether it is in tables, excel files, server logs, or 3rd party APIs. 3rd Party APIs: Pointillist has a large number of connectors using 3rd party APIs.