Machine Learning Goes Data-Centric

Updated: Sep 1, 2021

Practically anyone who was involved in machine learning should know Andrew Ng, co-founder of Coursera, a professor at Stanford, author of the most popular machine learning MOOC courses. Recently he launched a campaign advocating for more data-centric AI.


It's a bit different data-centric focus, than described in Fluree whitepapers, where the most emphasis is given on a consistency of the data quality, rather than make data linkable and shareable, but still, moving away from fancy models back to boring job of making data better, is the main thesis of his campaign.


Can Logosphere help to achieve this goal? We believe it can. By applying global semantic standards on data collected into the knowledge graph, verifying consistency of data with business model framework, we'll be able to increase data quality and help with accuracy and interpretability of the machine learning and AI models.


Watch Andrew's presentation about data centricity in AI:





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