Regularization Deep Learning models have so much flexibility and capacity that overfitting can be a serious problem,if the training dataset is not big enough. Sure it does well on the training set, but the learned network doesn't generalize to new ex…
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 odds of gradient descent converging to a lower training (and generalization) error) To get started, run…
1. Optimization Methods Gradient descent goes "downhill" on a cost function \(J\). Think of it as trying to do this: **Figure 1** : **Minimizing the cost is like finding the lowest point in a hilly landscape** At each step of the training, you u…
TensorFlow Tutorial Initialize variables Start your own session Train algorithms Implement a Neural Network 1. Exploring the Tensorflow Library To start, you will import the library: import math import numpy as np import h5py import matplotlib.pyplot…
