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In the previous video, we discussed using modern methods in data science and machine learning for challenging control systems with unknown dynamics, nonlinear systems, high-dimensional states, and limited measurements. This includes data-driven modeling, data-driven control, using machine learning for effective control laws, and optimization for optimal sensor and actuator placement. This overview focuses on using data science and machine learning for system identification, which will be a key part of the upcoming lectures in this series.
