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…
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…
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…
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…
