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深度学习问题记录:Initialization

He initialization

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Zero initialization

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axes
plt.title("Model with Zeros initialization")
axes = plt.gca()
axes.set_xlim([-1.5,1.5])
axes.set_ylim([-1.5,1.5])
plot_decision_boundary(lambda x: predict_dec(parameters, x.T), train_X, train_Y)
inf

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If you see "inf" as the cost after the iteration 0, this is because of numerical roundoff(数值四舍五入); a more numerically sophisticated implementation would fix this. But this isn't worth worrying about for our purposes.

随机初始化过大的缺点

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He initialization

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结论
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relu用He初始化,言外之意似乎是对于sigmoid和than用np.random.randn()*0.01就可以了???

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