mxnet gradient descent for linear regression, variable types error
I'm trying to implement a simple gradient descent for linear regression. It works normally if I compute the gradient manually (by using the analytical expression), but now i was trying to implement it with autograd from the mxnet module. This is the code from mxnet import autograd, np, npx npx.set_np() def main(): # learning algorithm parameters nr_epochs = 1000 alpha = 0.01 # read data, insert column of ones (to include bias with other parameters) data = pd.read_csv("dataset.txt", header=0, index_col=None, sep="\s+") data.insert(0, "x_0", 1, True) # insert column of "1"s as x_0 m = data.shape