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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning

By using the Livy REST APIs , SageMaker Studio users can also extend their interactive analytics workflows beyond just notebook-based scenarios, enabling a more comprehensive and streamlined data science experience within the Amazon SageMaker ecosystem. elasticmapreduce", "arn:aws:s3:::*.elasticmapreduce/*" elasticmapreduce", "arn:aws:s3:::*.elasticmapreduce/*"

Big data 100
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How VirtuSwap accelerates their pandas-based trading simulations with an Amazon SageMaker Studio custom container and AWS GPU instances

AWS Machine Learning

The challenge The VirtuSwap Minerva engine creates recommendations for optimal distribution of liquidity between different liquidity pools, while taking into account multiple parameters, such as trading volumes, current market liquidity, and volatilities of traded assets, constrained by a total amount of liquidity available for distribution.

APIs 123
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Detect and protect sensitive data with Amazon Lex and Amazon CloudWatch Logs

AWS Machine Learning

At the same time, it’s crucial to make sure these security measures don’t undermine the functionality and analytics critical to business operations. Sensitive data, such as name, account number, and phone number, should be tagged with a high classification level, indicating the need for stringent security measures.

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John Oechsle: How Do You Spell CRM Evolution? With 4 C’s

Bill Quiseng

Social media accounts might be inaccurate or outdated. If customer information is kept accurately and up to date, it can prove to be invaluable when used with predictive analytics technology. John Oechsle joined Swiftpage in July 2012 and currently serves as president and chief executive officer. By 1989, just 15 percent of U.S.

CRM 98
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Use Amazon SageMaker Studio with a custom file system in Amazon EFS

AWS Machine Learning

In addition to this, the solution expects that the AWS account in which the template is deployed already has the following configuration and resources: You should have a SageMaker Studio domain. Refer to Creating a trail for your AWS account for additional information. You need to create a mount target for each subnet.

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Build a multilingual automatic translation pipeline with Amazon Translate Active Custom Translation

AWS Machine Learning

With a background in AI/ML, data science, and analytics, Yunfei helps customers adopt AWS services to deliver business results. He designs AI/ML and data analytics solutions that overcome complex technical challenges and drive strategic objectives. About the authors Yunfei Bai is a Senior Solutions Architect at AWS.

APIs 79
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Fireside Chat: Natero Shares Tips for Customer Success

Satrix Solutions

Natero helps Customer Success Managers reduce churn, increase expansion, and manage more accounts. Read our interview: Evan Klein: How has the Customer Success industry changed since Natero was first founded in 2012? For example, high-value accounts can command more face time and personal attention. Customer data silos.

SaaS 60