浅谈python神经网络搭建

本文主要对python语言搭建神经网络进行了分析与实现,首先阐述了python语言及其发展,对其特点进行分析;而后探讨神经网络算法的基本构成及神经元的结构;最后,以BP神经网络为例,阐述了神经网络的实现步骤,编写代码对BP神经网络进行了构建与实现。通过运行程序,设置的两个参数发生明显改变,交叉熵值在不断减小,整个网络的精准在不断上升,预测结果更加准确。

this paper mainly analyzes and implements the construction of python neural network. Firstly, it expounds the development of python language and analyzes its characteristics. Then the basic structure of neural network algorithm and the structure of neurons are discussed. Finally, taking BP neural network as an example, the implementation steps of the neural network are described, and the code is written to construct and implement the BP neural network. By running the program, the two parameters set were significantly changed, the value of cross entropy was decreasing, the accuracy of the whole network was increasing, and the prediction results were more accurate.