Physics and the machine-learning "black box"

Machine-learning algorithms are often referred to as a "black box." Once data are put into an algorithm, it's not always known exactly how the algorithm arrives at its prediction. This can be particularly frustrating when things go wrong. A new mechanical engineering (MechE) course at MIT teaches students how to tackle the "black box" problem, through a combination of data science and physics-based engineering. In class 2.C01 (Physical Systems Modeling and Design Using Machine Learning), Professor George Barbastathis demonstrates how mechanical engineers can use their unique knowledge of physical systems to keep algorithms in check and develop more accurate predictions.