python derivative of mean squared error
def mse_loss_grad(y, t):
loss_ = np.sum(np.subtract(t-y))*(2/y.shape[0])
print("Derivative MSE: ".format(loss_)python derivative of mean squared error
def mse_loss_grad(y, t):
loss_ = np.sum(np.subtract(t-y))*(2/y.shape[0])
print("Derivative MSE: ".format(loss_)Copyright © 2021 Codeinu
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