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Reinventing the data experience: Use generative AI and modern data architecture to unlock insights

AWS Machine Learning

The combination of large language models (LLMs), including the ease of integration that Amazon Bedrock offers, and a scalable, domain-oriented data infrastructure positions this as an intelligent method of tapping into the abundant information held in various analytics databases and data lakes.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1

AWS Machine Learning

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at any single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository. Background.

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

AWS Machine Learning

The sample dataset we use in this post is a sampled version of the Diabetes 130-US hospitals for years 1999-2008 Data Set (Beata Strack, Jonathan P. For instructions on assigning permissions to the role, refer to Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference. His focus area is on data and analytics.

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Top 30 SaaS Companies in India

SmartKarrot

Indian SaaS enterprises deal with a wide variety of clients across finance, education, healthcare, and wellness. The services offered by CloudCherry include customer journey map , text analytics, integrations, predictive analytics, dashboards, actionable insights, and more. This article will help you –. Capillary Technologies.

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