摘要:
···python plt.title("Model with Adam optimization") axes = plt.gca() axes.set_xlim([-1.5,2.5]) axes.set_ylim([-1,1.5]) plot_decision_boundary(lambda x 阅读全文
摘要:
1. Optimization Methods Gradient descent goes "downhill" on a cost function \(J\). Think of it as trying to do this: **Figure 1** : **Minimizing the c 阅读全文
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Regularization Deep Learning models have so much flexibility and capacity that overfitting can be a serious problem,if the training dataset is not big 阅读全文
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Initialization 如何选择初始化方式,不同的初始化会导致不同的结果 好的初始化方式: 加速梯度下降的收敛(Speed up the convergence of gradient descent) 增加梯度下降 收敛成 一个低错误训练(和 普遍化)的几率(Increase the odd 阅读全文