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Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

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In this post, we look at how we can use AWS Glue and the AWS Lake Formation ML transform FindMatches to harmonize (deduplicate) customer data coming from different sources to get a complete customer profile to be able to provide better customer experience. The following diagram shows our solution architecture.

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IBM and business partner bring intelligent equipment maintenance to automotive company with IBM Maximo

IBM Journey to AI blog

Maintenance workers need to consume a lot of energy to check up the equipment data to understand and learn new skills, resulting in not only low maintenance efficiency, but also leading to a decline in employee satisfaction and loyalty.

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Transforming financial analysis with CreditAI on Amazon Bedrock: Octus’s journey with AWS

AWS Machine Learning Blog

By surrounding unparalleled human expertise with proven technology, data and AI tools, Octus unlocks powerful truths that fuel decisive action across financial markets. Visit octus.com to learn how we deliver rigorously verified intelligence at speed and create a complete picture for professionals across the entire credit lifecycle.

DevOps 69
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Prioritizing employee well-being: An innovative approach with generative AI and Amazon SageMaker Canvas

AWS Machine Learning Blog

SageMaker Data Wrangler has also been integrated into SageMaker Canvas, reducing the time it takes to import, prepare, transform, featurize, and analyze data. In a single visual interface, you can complete each step of a data preparation workflow: data selection, cleansing, exploration, visualization, and processing.

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

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It provides a single web-based visual interface where you can perform all ML development steps, including preparing data and building, training, and deploying models. AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, ML, and application development.

ML 123
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How Getir reduced model training durations by 90% with Amazon SageMaker and AWS Batch

AWS Machine Learning Blog

Overview of solution Five people from Getir’s data science team and infrastructure team worked together on this project. The project was completed in a month and deployed to production after a week of testing. We used GPU jobs that help us run jobs that use an instance’s GPUs. The following diagram shows the solution’s architecture.

BERT 121
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10 Best Sales Engagement Platforms (October 2023)

Unite.AI

Clearbit Capture, another valuable tool, focuses on lead capture on websites, auto-filling forms with data from Clearbit’s database to minimize form abandonment. Clearbit Capture and API : Facilitates lead capture and provides extensive API access for data integration.