Remove 2015 Remove Data Quality Remove ML
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Architect a mature generative AI foundation on AWS

Flipboard

Data quality is ownership of the consuming applications or data producers. Governance The two key areas of governance are model and data: Model governance Monitor model for performance, robustness, and fairness. Since 2013 he has helped AWS customers adopt AI/ML technology as a Solutions Architect.

AWS 140
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McKinsey QuantumBlack on automating data quality remediation with AI

Snorkel AI

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. The macro view will not be surprising.

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McKinsey QuantumBlack on automating data quality remediation with AI

Snorkel AI

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. The macro view will not be surprising.

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McKinsey QuantumBlack on automating data quality remediation with AI

Snorkel AI

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. The macro view will not be surprising.

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Extract non-PHI data from Amazon HealthLake, reduce complexity, and increase cost efficiency with Amazon Athena and Amazon SageMaker Canvas

AWS Machine Learning Blog

In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. It enables them to unlock the value of their data, identify trends, patterns, and predictions, and differentiate themselves from their competitors.

ML 100
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Why QBE Ventures invested in Snorkel AI

Snorkel AI

Training data quality is the single biggest determinant of model performance. Insurance data is typically highly inaccessible: reports suggest that 80% of insurance data is unstructured, unlabelled, and not ready for AI model training.

AI 52
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Why QBE Ventures invested in Snorkel AI

Snorkel AI

Training data quality is the single biggest determinant of model performance. Insurance data is typically highly inaccessible: reports suggest that 80% of insurance data is unstructured, unlabelled, and not ready for AI model training.

AI 52