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Best practices for building secure applications with Amazon Transcribe

AWS Machine Learning

Because these best practices might not be appropriate or sufficient for your environment, use them as helpful considerations rather than prescriptions. This content includes the security configuration and management tasks for the AWS services that you use. For more information about data privacy, see the Data Privacy FAQ.

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How to Communicate Effectively with Customers: Best Practices

Cincom

How CCM Software Streamlines Communication Customer communication management (CCM) software is a centralized suite of tools to develop, manage, and optimize digital and print communications across channels. Click here to read our blog, What is Customer Communication Management Software? and learn more.

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Common Challenges in Automated API Testing: Overcoming Obstacles with Expert Solutions

CSM Magazine

Automated API testing stands as a cornerstone in the modern software development cycle, ensuring that applications perform consistently and accurately across diverse systems and technologies. Continuous learning and adaptation are essential, as the landscape of API technology is ever-evolving.

APIs 52
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Drive efficiencies with CI/CD best practices on Amazon Lex

AWS Machine Learning

You liked the overall experience and now want to deploy the bot in your production environment, but aren’t sure about best practices for Amazon Lex. In this post, we review the best practices for developing and deploying Amazon Lex bots, enabling you to streamline the end-to-end bot lifecycle and optimize your operations.

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Secure Amazon SageMaker Studio presigned URLs Part 2: Private API with JWT authentication

AWS Machine Learning

In this post, we will continue to build on top of the previous solution to demonstrate how to build a private API Gateway via Amazon API Gateway as a proxy interface to generate and access Amazon SageMaker presigned URLs. The user invokes createStudioPresignedUrl API on API Gateway along with a token in the header.

APIs 81
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Use AWS PrivateLink to set up private access to Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them for specific applications. It allows developers to build and scale generative AI applications using FMs through an API, without managing infrastructure.

APIs 125
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Customize Amazon Textract with business-specific documents using Custom Queries

AWS Machine Learning

Custom Queries is easy to integrate in your existing Textract pipeline and you continue to benefit from the fully managed intelligent document processing features of Amazon Textract without having to invest in ML expertise or infrastructure management. Refer to Best Practices for Queries to draft queries applicable to your use case.

APIs 101