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

AWS Machine Learning

Our solution describes an AWS DeepRacer environment configuration using the AWS CDK to accelerate the journey of users experimenting with SageMaker log analysis and reinforcement learning on AWS for an AWS DeepRacer event. The following diagram illustrates the solution architecture.

Scripts 94
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How Accenture is using Amazon CodeWhisperer to improve developer productivity

AWS Machine Learning

In this post, we illustrate how Accenture uses CodeWhisperer in practice to improve developer productivity. Accenture is using Amazon CodeWhisperer to accelerate coding as part of our software engineering best practices initiative in our Velocity platform,” says Balakrishnan Viswanathan, Senior Manager, Tech Architecture at Accenture.

Scripts 98
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Amazon Bedrock Custom Model Import now generally available

AWS Machine Learning

If you have a different format, you can potentially use Llama convert scripts or Mistral convert scripts to convert your model to a supported format. The fine-tuning scripts are based on the scripts provided by the Llama fine-tuning repository. from sagemaker.s3 3B model Now, we’ll fine-tune the Llama 3.2

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

AWS Machine Learning

We demonstrate how to use CI/CD the low-code/no-code tools code to integrate it into your MLOps environment, while adhering with MLOps best practices. You can also add your own Python scripts and transformations to customize workflows. Solutions Architect at Amazon Web Services (AWS). Python code file.