Multiple times over the last decade, this column has covered the issue of the importance of data quality in decision making, both by executives as well as machines. Back in 2014, when the “big data” ...
Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Intelligent organizations prioritize investments in machine learning and real-time data to ...
The flexibility, agility and ultimate cost of machine learning projects can be significantly impacted by data logistics and dependencies, according to Jim Scott, VP, Enterprise Architecture, at MapR.
Machine learning is being applied in recommendation engines, marketing automation, financial fraud detection, language translation, and text-to-speech applications. Pexels Apple recently announced ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More “An underlying issue that most enterprise organizations struggle with is ...
Even as machine learning and artificial intelligence are drawing substantial attention in health care, overzealousness for these technologies has created an environment in which other critical aspects ...
Poor data quality is enemy number one to the widespread, profitable use of machine learning. While the caustic observation, “garbage-in, garbage-out” has plagued analytics and decision-making for ...
“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Ken Rona, chief data scientist at ...
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