Not very important and for a learning project I find using cvxpy a better idea as it's more readable ( like you did ) but: Solving the full quadratic optimizat

Not very important and for a learning project I find using cvxpy a better idea as it's more readable ( like you did ) but: Solving the full quadratic optimization problem for SVMs in basically impossible to do. You are forming an n^2 matrix, so I'm going to let you imagine what happens when n = 100 000. Using people use either approximation methods ( Incomplete Cholesky, Nystrom ) or do it exactly but iteratively ( SMO, Pegasos... ) I'm implementing them for class right now so it's still fresh in my head haha