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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 exploration of markdown and HTML syntax trees. Documenting my experience creating rehype-prism-plus, a syntax highlighting plugin that creates pretty code blocks.- Published on
This post introduces Automated Market Makers, a key protocol powering decentralized exchanges.- Published on
A good project is only one part of the puzzle. Getting stars is really all about marketing and promoting it. A guide on growth hacking a Github project.