Hosting a private PyPI server for Amazon SageMaker Studio notebooks in a VPC

Favorite Amazon SageMaker Studio notebooks provide a full-featured integrated development environment (IDE) for flexible machine learning (ML) experimentation and development. Security measures secure and support a versatile and collaborative environment. In some cases, such as to protect sensitive data or meet regulatory requirements, security protocols require that public internet access

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Shared by AWS Machine Learning January 12, 2021

AWS Announces the global expansion of AWS CCI Solutions

Favorite We’re excited to announce the global availability of AWS Contact Center Intelligence (AWS CCI) solutions powered by AWS AI Services and made available through the AWS Partner Network. AWS CCI solutions enable you to leverage AWS machine learning (ML) capabilities with your current contact center provider to gain greater

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Shared by AWS Machine Learning January 12, 2021

Controlling and auditing data exploration activities with Amazon SageMaker Studio and AWS Lake Formation

Favorite Highly-regulated industries, such as financial services, are often required to audit all access to their data. This includes auditing exploratory activities performed by data scientists, who usually query data from within machine learning (ML) notebooks. This post walks you through the steps to implement access control and auditing capabilities

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Shared by AWS Machine Learning December 22, 2020