python 搭建神经网络 示例

以下是一个简单的示例，展示如何使用 Python 搭建神经网络：

import numpy as np

# 定义神经网络类
class NeuralNetwork:
    def __init__(self, input_size, hidden_size, output_size):
        # 初始化权重
        self.W1 = np.random.randn(input_size, hidden_size)
        self.W2 = np.random.randn(hidden_size, output_size)
    
    def forward(self, X):
        # 前向传播
        self.z = np.dot(X, self.W1)
        self.z2 = self.sigmoid(self.z)
        self.z3 = np.dot(self.z2, self.W2)
        y_hat = self.sigmoid(self.z3)
        return y_hat
    
    def sigmoid(self, x):
        # sigmoid 激活函数
        return 1 / (1 + np.exp(-x))

# 创建神经网络实例
input_size = 2
hidden_size = 3
output_size = 1
nn = NeuralNetwork(input_size, hidden_size, output_size)

# 输入数据
X = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
y = np.array([[0], [1], [1], [0]])

# 训练神经网络
learning_rate = 0.1
epochs = 10000

for i in range(epochs):
    # 前向传播