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Advances in Data Analytics Are Rapidly Transforming Nursing

Smart Data Collective

Big data is especially important for the nursing sector. A 2017 study from Harvard Medical School discusses some of the changes big data has created for nurses. You can’t even sleep uninterrupted without getting woken up every few hours for a test or a check-in. It’s a big deal. So, what’s out there?

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Digital listening reveals 3 leading innovation drivers

CIO Business Intelligence

higher [in 2022] than in 2017.” The inherent capabilities of AI–to process vast amounts of data and use learned intelligence to make decisions with extraordinary speed–enable opportunities uncovered through digital listening. McKinsey & Company’s 2022 Global Survey on AI says , “AI adoption globally is 2.5x

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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

They will need two different implementations, it is quite likely that you will end up with two sets of metrics (more people focused for mobile apps, more visit focused for sites). In this post we will look mobile sites first, both data collection and analysis, and then mobile applications. And again, a custom set of metrics.

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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. 2018-06-21).

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. Insufficient training data in the minority class — In domains where data collection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large. Chawla et al.,

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Measuring Validity and Reliability of Human Ratings

The Unofficial Google Data Science Blog

Once we’ve answered that, we will then define and use metrics to understand the quality of human-labeled data, along with a measurement framework that we call Cross-replication Reliability or xRR. Last, we’ll provide a case study of how xRR can be used to measure improvements in a data-labeling platform.

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Techniques for Collecting, Prepping, and Plotting Data: Predicting Social Media-Influence in the NBA

Domino Data Lab

The first step to collecting all of the data is to figure out which data source to collect first, and where to get it. Knowing that the ultimate goal is to compare the social-media influence and power of NBA players, a great place to start is with the roster of the NBA players in the 2016–2017 season. 35,vjust=1).