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Pandemic relief and restart industry solutions

Talkdesk

Meanwhile, people are left wondering when and how to get their vaccine, and when and how to obtain a PPP loan to keep their businesses afloat. Here’s how: Small Business Lending Solution. Learn more about the Small Business Lending Solution. And critically, we can provide this help immediately.

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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.

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How Accenture is using Amazon CodeWhisperer to improve developer productivity

AWS Machine Learning

CodeWhisperer is powered by a Large Language Model (LLM) that is trained on billions of lines of code, and as a result, has learned how to write code in 15 programming languages. In this post, we illustrate how Accenture uses CodeWhisperer in practice to improve developer productivity.

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

AWS Machine Learning

The following diagram illustrates the solution architecture. 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.

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Bring SageMaker Autopilot into your MLOps processes using a custom SageMaker Project

AWS Machine Learning

This post showcases how to have a repeatable process with low-code tools like Amazon SageMaker Autopilot such that it can be seamlessly integrated into your environment, so you don’t have to orchestrate this end-to-end workflow on your own. For instructions on how to include or remove transformations in Data Wrangler, refer to Transform Data.

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Amazon Bedrock Custom Model Import now generally available

AWS Machine Learning

In this section, we’ll show you how to fine-tune the Llama 3.2 You can refer to the console screenshots in the earlier section for how to import a model using the Amazon Bedrock console. Best practices to consider: This feature brings significant advantages for hosting your fine-tuned models efficiently.

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Automate cloud security vulnerability assessment and alerting using Amazon Bedrock

AWS Machine Learning

get("text") return message It’s crucial to perform prompt engineering and follow prompting best practices in order to avoid hallucinations or non-coherent responses from the LLM. The following sample code shows how to use the Step Functions optimized integration with Lambda and Amazon SNS.

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