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

AWS Machine Learning

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. Just like DevOps combines development and operations for software engineering, MLOps combines ML engineering and IT operations.

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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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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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Calabrio Charts Record Year-on-Year UK Growth as Demand for Cloud Technology Soars During Lockdown

CSM Magazine

“Coupled with businesses operating solely online, we have also seen strong demand across the board from more traditional sectors such as finance, insurance, retail, consumer goods, local and central government departments. These organisations require an innovative yet reliable solution to help them manage unprecedented levels in demand.”.

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

AWS Machine Learning

We recommend following certain best practices that are highlighted through the concepts detailed in the following resources: Building secure machine learning environments with Amazon SageMaker Setting up secure, well-governed machine learning environments on AWS Clone the GitHub repo into your environment.

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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. Data Wrangler provides an end-to-end solution to import, prepare, transform, featurize, and analyze data. You can also add your own Python scripts and transformations to customize workflows.