importnumpyasnp # ... code from previous section here classOurNeuralNetwork: ''' A neural network with: - 2 inputs - a hidden layer with 2 neurons (h1, h2) - an output layer with 1 neuron (o1) Each neuron has th
import operator import time def createData(dim = 200, cnoise = 0.2): ''' 生成数据集 ''' x, y = sklearn.datasets.make_moons(dim, noise = cnoise) plt.scatter(x[:,0], x[:,1], s = 40, c=y, cmap=plt.cm.Spectral) return x,y def initSuperParameter(x): ''' 初始化超参数 ...
importnumpyasnp # ... code from previous section here classOurNeuralNetwork: ''' A neural network with: - 2 inputs - a hidden layer with 2 neurons (h1, h2) - an output layer with 1 neuron (o1) Each neuron has the same weights and bias: - w = [0, 1] - b = 0 ''' def_...
In this step-by-step tutorial, you'll build a neural network from scratch as an introduction to the world of artificial intelligence (AI) in Python. You'll learn how to train your neural network and make accurate predictions based on a given dataset.
这第一个部分是BP神经网络的建立 参数选取参照论文:基于数据挖掘技术的股价指数分析与预测研究_胡林林 importmathimportrandomimporttushare as tsimportpandas as pd random.seed(0)defgetData(id,start,end): df=ts.get_hist_data(id,start,end) DATA=pd.DataFrame(columns=['rate1','rate2','rate3','pos...
code from previous section here class OurNeuralNetwork: ''' A neural network with: - 2 inputs - a hidden layer with 2 neurons (h1, h2) - an output layer with 1 neuron (o1) Each neuron has the same weights and bias: - w = [0, 1] - b = 0 ''' def __init__(self): weigh...
# ... code from previous section here classOurNeuralNetwork: ''' A neural network with: - 2 inputs - a hidden layer with 2 neurons (h1, h2) - an output layer with 1 neuron (o1) Each neuron has the same weights and bias:
"""network.py ~~~ A module to implement the stochastic gradient descent learning algorithm for a feedforward neural network. Gradients are calculated using backpropagation. Note that I have focused on making the code simple, easily readable, and easily modifiable. It is not optimized, and omits...
这节里用代码演示一遍 Neural Networks and Deep Learning 这门课的核心思想,具体例子使用 Coursera 这门课 L 层 Neural Network 的例子。 可运行的源代码可以从这里下载: kakage/Deep-Learninggithub.com/kakage/Deep-Learning 这里我们建造一个 L 层 Neural Network 的模型去判断图片是猫还是不是猫。
blob/master/ part2_neural_network_mnist_data.ipynb 也可以在以下的链接中找到开发代码,通过这个链接,可以看到以前的版本: commits/master/part2_neural_network_mnist_data.ipynb # python notebook for Make Your Own Neural Network# code for a 3-layer neural network, and code for learning the MNISTdata...