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Automate cloud security vulnerability assessment and alerting using Amazon Bedrock

AWS Machine Learning

You need to establish proper security guardrails in the cloud environment and create a proactive monitoring practice to strengthen your cloud security posture and maintain required compliance standards. GuardDuty integrates with Amazon EventBridge by creating an event for EventBridge for new generated vulnerability findings.

APIs 72
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Amazon Bedrock Custom Model Import now generally available

AWS Machine Learning

Best practices to consider: This feature brings significant advantages for hosting your fine-tuned models efficiently. The maximum concurrency that you can expect for each model will be 16 per account. The default import quota for each account is three models. See Amazon Bedrock Recipes and GitHub for more examples.

APIs 139
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Streamline Sales Processes with Enterprise CPQ

Cincom

Integration with Existing Systems: APIs facilitate data sharing between CPQ and other core platforms like CRM, ERP, accounting, e-commerce, and more. Configurable rules encode compliance requirements and best practices to guide users and skip unnecessary steps.

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Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

AWS Machine Learning

With the help of the AWS CDK, we can version control our provisioned resources and have a highly transportable environment that complies with enterprise-level best practices. Make sure you have the credentials and permissions to deploy the AWS CDK stack into your account.

Scripts 85
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Enhance call center efficiency using batch inference for transcript summarization with Amazon Bedrock

AWS Machine Learning

We also explore best practices for optimizing your batch inference workflows on Amazon Bedrock, helping you maximize the value of your data across different use cases and industries. Prerequisites To use the batch inference feature, make sure you have satisfied the following requirements: An active AWS account.

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Driving advanced analytics outcomes at scale using Amazon SageMaker powered PwC’s Machine Learning Ops Accelerator

AWS Machine Learning

However, putting an ML model into production at scale is challenging and requires a set of best practices. Integrations with CI/CD workflows and data versioning promote MLOps best practices such as governance and monitoring for iterative development and data versioning.

Analytics 127
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Reinvent personalization with generative AI on Amazon Bedrock using task decomposition for agentic workflows

AWS Machine Learning

In parallel, OneCompany maintains a market research repository gathered by their researchers, offers industry-specific services outlined in documents, and has compiled approved customer testimonials. UX/UI designers have established best practices and design systems applicable to all of their websites.