Regularization, Machine Learning, Convex Optimization, Lagrangian, Ml So Good.
standard deviation) This is the moment of truth, w1 and w2 could grow arbitrary large to fit the distribution, which would make our model complex and would cause overfitting, which meant that we were trying to solve an unconstrained problem, or simply this was an unconstrained optimization. One