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Structural Evolutions in Data

O'Reilly on Data

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

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

BizAcuity

2008: Microsoft announces Windows Azure (PaaS) with Azure Blob storage (S3 competitor). AWS rolls out SageMaker, designed to build, train, test and deploy machine learning (ML) models. Businesses find the need to manage unstructured data efficiently as a major business problem.