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Preprocess and fine-tune LLMs quickly and cost-effectively using Amazon EMR Serverless and Amazon SageMaker

AWS Big Data

The Common Crawl corpus contains petabytes of data, regularly collected since 2008, and contains raw webpage data, metadata extracts, and text extracts. In addition to determining which dataset should be used, cleansing and processing the data to the fine-tuning’s specific need is required. It is continuously updated.

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Use your corporate identities for analytics with Amazon EMR and AWS IAM Identity Center

AWS Big Data

About the Authors Pradeep Misra is a Principal Analytics Solutions Architect at AWS. He works across Amazon to architect and design modern distributed analytics and AI/ML platform solutions. He is passionate about solving customer challenges using data, analytics, and AI/ML.

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How The Cloud Made ‘Data-Driven Culture’ Possible | Part 1

BizAcuity

2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. The platform is built on S3 and EC2 using a hosted Hadoop framework. An efficient big data management and storage solution that AWS quickly took advantage of. To be continued.