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Translating responsible AI principles to create VerifyML. User feedback, design decisions and architecture choices in creating our responsible AI solution.
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Fairness is messy and complicated. Attempts to distil it down to a single metric is unhelpful and counter-productive. As business owners and model developers we should embrace the struggle in trying to apply fairness in artificial intelligence and data analytics models.- Published on
An explanation of the challenges of graph anonymisation and the difficulty of striking a balance between usefulness and anonymity. Written as a response to Singapore's TraceTogether privacy saga- Published on
An exploratory analysis of a jobs posting dataset along with some tidbits on the Singapore hiring landscape- Published on
SG Dashboard is now released and updated with Q3's economic results- Published on
An R shiny application with Leaflet- Published on
A tutorial on using Leaflet in R for geospatial visualisation- Published on
Exploring the changes in religious beliefs in Singapore between 2000 to 2015- Published on
Examining the spatial distribution of Singapore's population- Published on
updated the SG-Dashboard with 2Q 2017 numbers