The road to artificial intelligence is paved with calculus

The three adjectives served as parting wisdom for a dozen William & Mary students seated in McGlothlin-Street Hall. White was wrapping up the final class of the semester for his course "Neural Networks for Machine Learning." A 2017 Ph.D. graduate of W&M's Department of Computer Science, White returned to his alma mater to teach after he heard the department wanted to offer another course on machine learning, a key subset of artificial intelligence. "I believed neural networks could serve as the perfect backdrop for a class studying what learning from data means and how to do it well," White said. "Since the fundamentals draw from calculus, probability, statistics, and linear algebra, the first part of the course is pretty intense, but I was interested in returning to teach because I had some ideas on how to manage this complexity."