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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. Many businesses already have data scientists and ML engineers who can build state-of-the-art models, but taking models to production and maintaining the models at scale remains a challenge.

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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.

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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. Zdenko likes to bike to the office and enjoys pleasant walks in nature.

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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. Data Wrangler provides an end-to-end solution to import, prepare, transform, featurize, and analyze data. Solutions Architect at Amazon Web Services (AWS).