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.
Technical Debt describes what results when development teams take conscious actions to expedite the delivery of a piece of functionality or a project which later needs to be remediated via refactoring.
Building machine learning projects can give you a much more comprehensive education about how they work.
As this century progresses, businesses are discovering that the most incredible way to gain the best customer service is to know them deeply. With AI… Read More »Enriching Customer Service Using Sentiment Analysis
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I wrote this article for machine learning and analytic professionals in general. Actually, I describe a new visual, simple, intuitive method for supervised classification. It… Read More »The Riemann Hypothesis in One Picture
Data annotation is at the forefront of the recent revolution in healthcare AI, driving continuous progress in the field through continuous innovation through the idea… Read More »Datasets and Data Annotation — The Building Blocks for Healthcare AI
Anti-money laundering (AML) and know-your-customer (KYC) compliance might be transformed by artificial intelligence (AI). Artificial intelligence systems may also mine vast amounts of data through… Read More »How AI is Stopping Money Laundering
After 25 Years of Coding in C And Perl. As an independent author/researcher, there is of course nothing in my “job description” that says I… Read More »Lessons Learned from Writing My First Python Script
