Function loss

05_1_gradientdescent_manually.py:19–20

(y, y_pred)

# loss = MSE
def loss(y, y_pred):
    return ((y_pred - y)**2).mean()

# J = MSE = 1/N * (w*x - y)**2
# dJ/dw = 1/N * 2x(w*x - y)