Abstract: Learning-based motion planning methods have shown significant promise in enhancing the efficiency of traditional algorithms. However, they often face performance degradation in novel ...
Machine Learning course from Stanford University on Coursera. function J = computeCost(X, y, theta) # Initialize some useful values m = length(y); # number of training examples # You need to return ...
This project develops machine learning ML surrogate models to approximate the performance of a binary distillation column. Process data is generated using DWSIM, an open-source process simulator, by ...
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