Remove Data Quality Remove Measurement Remove Metrics Remove Uncertainty
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What you need to know about product management for AI

O'Reilly on Data

Machine learning adds uncertainty. Underneath this uncertainty lies further uncertainty in the development process itself. There are strategies for dealing with all of this uncertainty–starting with the proverb from the early days of Agile: “ do the simplest thing that could possibly work.”

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What’s New and What’s Next in 2023 for HPC

CIO Business Intelligence

Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI). Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics? There’s always room to grow, and Intel is ready to help.

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Measuring Validity and Reliability of Human Ratings

The Unofficial Google Data Science Blog

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. How do we think about the quality of human ratings, and how do we quantify our understanding is the subject of this post. While human-labeled data is critical to many important applications, it also brings many challenges.

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Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

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AI Product Management After Deployment

O'Reilly on Data

Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics. But in practice, it is common for model I/O validation steps to be added later, when scaling an AI product.

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Human-centered design and data-driven insights elevate precision in government IT modernization

IBM Big Data Hub

Government executives face several uncertainties as they embark on their journeys of modernization. How to quantify the impact : Quantify, articulate and measure the expected long-term benefit of a capability to justify the investment. Through the analysis of collected data, potential opportunities for improvement are uncovered.

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Fact-based Decision-making

Peter James Thomas

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? These and other areas are covered in greater detail in an older article, Using BI to drive improvements in data quality.

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