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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

MLOps – Model monitoring and ongoing governance wasn’t tightly integrated and automated with the ML models. Reusability – Without reusable MLOps frameworks, each model must be developed and governed separately, which adds to the overall effort and delays model operationalization.

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

AWS Machine Learning

Data and model management provide a central capability that governs ML artifacts throughout their lifecycle. Integrations with CI/CD workflows and data versioning promote MLOps best practices such as governance and monitoring for iterative development and data versioning. It enables auditability, traceability, and compliance.

Analytics 128
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Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

AWS Machine Learning

Prerequisites In order to provision ML environments with the AWS CDK, complete the following prerequisites: Have access to an AWS account and permissions within the Region to deploy the necessary resources for different personas. Make sure you have the credentials and permissions to deploy the AWS CDK stack into your account.

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EVERYTHING YOU NEED TO KNOW ABOUT STIR/SHAKEN

Hodusoft

Many government organizations use them to send important and urgent updates. In later years, STIR/SHAKEN was developed jointly by the SIP Forum and the Alliance for Telecommunications Industry Solutions (ATIS) to efficiently implement the Internet Engineering Task Force (IETF). Now, not all robocalls are bad.

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

AWS Machine Learning

Supply Chain Disruptions The COVID-19 pandemic has highlighted the vulnerability of global supply chains, and the EV industry has not been. Regulatory Frameworks and Incentives Regulatory frameworks and government incentives play a critical role in promoting EV. The AWS Command Line Interface (AWS CLI) installed.

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

AWS Machine Learning

Every organization has its own set of standards and practices that provide security and governance for their AWS environment. Prerequisites This walkthrough includes the following prerequisites: An AWS account. In the following sections, we proceed with each of these steps in more detail and explore the project details page.