Machine Learning, a subfield of computer science, involves the development of mathematical algorithms that discover knowledge from specific data sets, and then "learn" from the data in an iterative fashion that allows predictions to be made. Today, Machine Learning has a wide range of applications, including natural language processing, search engine functionality, medical diagnosis, credit card fraud detection, and stock market analysis.
The Engineering in Medicine
When the National Academy of Engineering announced its 14 grand challenges in 2008, it noted, The century ahead poses challenges as formidable as any from millennia past. For engineering, these challenges present opportunities to design and develop technologies that are game-changing and have global impact. It is no surprise that three of the challenges on the list were specifically at the interface of engineering with medicine and health: advance health informatics; engineer better medicines; and reverse-engineer the brain.
To celebrate its rich history of discovery and innovation through the years, Columbia Engineering is hosting a thought-provoking symposium—Columbia's Engineering Renaissance: Foundation for the Future—on Friday, November 14, from 2:00 p.m. to 4:00 p.m. in Roone Arledge Auditorium.