Remove Accountability Remove Groups Remove industry solution
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23 Inspiring Women to Watch in 2023

TechSee

Serpil Timuray – CEO Europe Cluster and Member of Group Executive Committee, Vodafone – Serpil inspires us with her advocacy to close the global digital divide. Tabinda Kahn, TELUS International – Tabinda leads GTM activities for TELUS International as their Senior Digital Solutions Product Marketing Manager.

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Automated exploratory data analysis and model operationalization framework with a human in the loop

AWS Machine Learning

According to a Forbes survey , there is widespread consensus among ML practitioners that data preparation accounts for approximately 80% of the time spent in developing a viable ML model. This walkthrough includes the following prerequisites: An AWS account. Run the following cells to create your feature group name.

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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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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Implement group-based security for dashboard and analysis access control. Across accounts, automate deployment using export and import dataset, data source, and analysis API calls provided by QuickSight. About the Authors Stephen Randolph is a Senior Partner Solutions Architect at Amazon Web Services (AWS).

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Run your local machine learning code as Amazon SageMaker Training jobs with minimal code changes

AWS Machine Learning

You can include environment variables such as VPC, subnets, and security groups to launch SageMaker training jobs in the environment.yml file. Shikhar aids in architecting, building, and maintaining cost-efficient, scalable cloud environments for the organization, and supports the GSI partner in building strategic industry solutions on AWS.

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

AWS Machine Learning

Prerequisites This walkthrough includes the following prerequisites: An AWS account. Model groups This tab lists groups of model versions that were created by pipeline runs in the project. You can choose the model group to access the latest version of the model.