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How Carrier predicts HVAC faults using AWS Glue and Amazon SageMaker

AWS Machine Learning Blog

In this post, we show how the Carrier and AWS teams applied ML to predict faults across large fleets of equipment using a single model. We first highlight how we use AWS Glue for highly parallel data processing. This dramatically reduces the size of data while capturing features that characterize the equipment’s behavior.

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Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence

AWS Machine Learning Blog

The IDP Well-Architected Lens is intended for all AWS customers who use AWS to run intelligent document processing (IDP) solutions and are searching for guidance on how to build secure, efficient, and reliable IDP solutions on AWS. AWS might periodically update the service limits based on various factors.

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Build an automated insight extraction framework for customer feedback analysis with Amazon Bedrock and Amazon QuickSight

AWS Machine Learning Blog

The customer review analysis workflow consists of the following steps: A user uploads a file to dedicated data repository within your Amazon Simple Storage Service (Amazon S3) data lake, invoking the processing using AWS Step Functions. The raw data is processed by an LLM using a preconfigured user prompt.

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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

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Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. If you’re familiar with SageMaker and writing Spark code, option B could be your choice.

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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning Blog

Central model registry – Amazon SageMaker Model Registry is set up in a separate AWS account to track model versions generated across the dev and prod environments. with administrative privileges installed on AWS Terraform version 1.5.5 After the key is provisioned, it should be visible on the AWS KMS console.

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40 Must-Know Data Science Skills and Frameworks for 2023

ODSC - Open Data Science

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. Research Why should a data scientist need to have research skills, even outside of academia you ask?

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Enabling production-grade generative AI: New capabilities lower costs, streamline production, and boost security

AWS Machine Learning Blog

Organizations that want to build their own models or want granular control are choosing Amazon Web Services (AWS) because we are helping customers use the cloud more efficiently and leverage more powerful, price-performant AWS capabilities such as petabyte-scale networking capability, hyperscale clustering, and the right tools to help you build.

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