Machine Learning: What is it and Why it Matters
Because of new computing technologies, machine learning today is not like machine learning of the past. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It’s a science that’s not new – but one that has gained fresh momentum.
Ida Byrd-Hill is a futurist, economist and CEO of Automation Workz, a cybersecurity reskilling and diversity consulting firm. She is author of Invisible Talent Market, a Black Labor Economics History book. She holds an MBA from the Jack Welch Management Institute at Strayer University, with a specialization in People Management/Strategy and a BA Economics from the University of Michigan- Ann Arbor. Byrd-Hill has appeared in Associated Press, BBC, Crain’s Business Detroit, CW Street Beat, Cybercrime Magazine, Daytime NBC, Detroit News, Detroit Free Press, Essence Magazine, Good Morning America, Let It Rip, Michigan Chronicle, Model D, NPR, PBS, and X-conomy. www.autoworkz.org/diverse-lens
