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The ethics of data flow

O'Reilly on Data

Facebook asked Cambridge Analytica to delete the data back in 2015, but apparently did nothing to determine whether the data was actually deleted, or shared further. Once data has started flowing, it is very difficult to stop it. Data flows can be very complex. What might that responsibility mean?

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Drug Discovery Needs AI To Discover More Treatments

Smart Data Collective

In a report on the failure rates of drug discovery efforts between 2013 and 2015, Richard K. To bring costs down and encourage further experimentation, artificial intelligence can study hundreds or thousands of patient records in search of the biomarkers the drug intends to target.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. Our experimentation platform supports this kind of grouped-experiments analysis, which allows us to see rough summaries of our designed experiments without much work.

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AI on the mainframe? IBM may be onto something

CIO Business Intelligence

billion in 2015 to less than $6.5 It’s a natural fit and will be interesting to see how these ensemble AI models work and what use cases will go from experimentation to production,” says Dyer. billion in 2023 — with periodic spikes whenever IBM has introduced a new mainframe generation, Gartner claims.

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New Format for The Bar Chart Reference Page

The Data Visualisation Catalogue

Journal of Experimental Psychology: Applied, 4 (2), 119–138. Skau, D., & Kosara, R. Eurographics Conference on Visualization (EuroVis). An Evaluation of the Impact of Visual Embellishments in Bar Charts. Harrison, L., & Kosara, R. Eurographics Conference on Visualization (EuroVis) , 34. Bar charts and box plots.

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6 enterprise DevOps mistakes to avoid

CIO Business Intelligence

Driven by the development community’s desire for more capabilities and controls when deploying applications, DevOps gained momentum in 2011 in the enterprise with a positive outlook from Gartner and in 2015 when the Scaled Agile Framework (SAFe) incorporated DevOps.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

Instead, we focus on the case where an experimenter has decided to run a full traffic ramp-up experiment and wants to use the data from all of the epochs in the analysis. When there are changing assignment weights and time-based confounders, this complication must be considered either in the analysis or the experimental design.