Computational approach where algorithms learn patterns from data without being explicitly programmed with fixed equations. ML can model nonlinear relationships, detect subtle correlations, and improve over time as more data is collected. In CEA, ML is used for predicting yield, optimizing fertigation, detecting stress, and anomaly detection.
