深度学习网络误差的相关内容

[深度学习入门]基于Python的理论与实现[感知机、神经网络、误差反向传播法及相关技巧]（二）

第四章：神经网络的学习通常要解决某个问题时，人们习惯以自己的经验和直觉来分析问题找出规律，然后反复试验推进。 “学习”是指从训练数据中自动获取最优权重参数的过程。机器学习在前期收集问题的各项特征数据，用模型从数据中发现答案，争取避免人为介入。深度...

[深度学习入门]基于Python的理论与实现[感知机、神经网络、误差反向传播法及相关技巧]（一）

一、前言本文是本人在认真学习完[日]斋藤康毅所著《深度学习入门-基于Python的理论与实现》(因为封面上有条鱼，以下皆用《鱼书》代称之)后的学习心得与体会。至于为什么要把写成文字记录下来呢，一是为了我后续的学习方便快速地回忆之前的知识点，一是为了给同样在学习这本《鱼书》的朋友们提供一...

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深度学习入门（9）神经网络Affine与Softmax层的计算图表示方式及其误差反向传播的代码实现

1 Affine与Softmax层的实现1.1 Affine层神经元的加权和可以用 Y = np.dot(X, W) + B计算出来。然后，Y 经过激活函数转换后，传递给下一层。这就是神经网络正向传播的流程。神经网络的正向传播中进行的矩阵的乘积运算在几何学领域被称为“仿射变换” 。将进行仿...

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更新时间 2024-02-20 13:37:21

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