Knowledge graphs are network graphs that link related concepts and properties together to create a form of inferencing engine, with knowledge engineering being the programming aspect of graph usage. Explore how knowledge graphs are created and queried, how they are used as part of a broader form of enterprise metadata management, and how they tie into ML and the IoT.
Models are simplification or approximation of reality and hence they will not capture all of reality. “All models are wrong, but some are useful” is… Read More »Does "All models are wrong, but some are useful" quote apply to Machine learning models?
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Tips Don’t try to put the cart before the horse: realize that efficient data preparation (and thus interoperable standards) and data quality, especially in the… Read More »Implementing Knowledge Graphs in Enterprises – Some Tips and Trends
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This article was written by Lance Whitney. An update to Google’s mobile app and website lets you search for symptoms and receive a list of… Read More »Google's Knowledge Graph Identifies your Medical Symptoms
These days, many organisations have begun to develop their own knowledge graphs. One reason might be to build a solid basis for various machine learning… Read More »A Standard to build Knowledge Graphs: 12 Facts about SKOS
