Temple University 3 credits CIS
Neural networks provide powerful techniques to model and control nonlinear and complex systems. This graduate-level course aims to introduce deep neural networks, including fundamental neural network architectures and advanced models. The student will learn the state-of-the-art deep neural networks, hands-on experiences with neural network simulators applied to classification and prediction problems, and cutting-edge research topics. Note: To register for this course, students should have earned a grade of "C" or better in college-level Python Programming/MATLAB Programming, Machine Learning, and Algebra.
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