機器學習第二課

梯度下降算法: Repeat { θ j = θ j − α ∂ ∂ θ j J ( θ 0 , θ 1 . . . θ n ) \theta_j=\theta_j-\alpha\frac{\partial}{\partial\theta_j}J(\theta_0,\theta_1...\theta_n) θj​=θj​−α∂θj​∂​J(θ0​,θ1​...θn​) }simultaneousl

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