深度学习PYTHON算法相关课件_深度学习_人工智能/神经网络/深度学习

<html xmlns="http://www.w3.org/1999/xhtml"> <head> <meta charset="utf-8"> <meta name="generator" content="pdf2htmlEX"> <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> <link rel="stylesheet" href="https://static.pudn.com/base/css/base.min.css"> <link rel="stylesheet" href="https://static.pudn.com/base/css/fancy.min.css"> <link rel="stylesheet" href="https://static.pudn.com/prod/directory_preview_static/627a8cf45981aa38ef363dcd/raw.css"> <script src="https://static.pudn.com/base/js/compatibility.min.js"></script> <script src="https://static.pudn.com/base/js/pdf2htmlEX.min.js"></script> <script> try{ pdf2htmlEX.defaultViewer = new pdf2htmlEX.Viewer({}); }catch(e){} </script> <title></title> </head> <body> <div id="sidebar" style="display: none"> <div id="outline"> </div> </div> <div id="pf1" class="pf w0 h0" data-page-no="1"><div class="pc pc1 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/627a8cf45981aa38ef363dcd/bg1.jpg"><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">深度学习</div><div class="t m0 x2 h3 y2 ff2 fs1 fc0 sc0 ls0 ws0">2017 年 9 月 4 日</div></div><div class="pi" data-data='{"ctm":[1.904762,0.000000,0.000000,1.904762,0.000000,0.000000]}'></div></div> </body> </html>

<div id="pf3" class="pf w0 h0" data-page-no="3"><div class="pc pc3 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/627a8cf45981aa38ef363dcd/bg3.jpg"><div class="t m0 x3 h5 y4 ff1 fs3 fc0 sc0 ls0 ws0">目录</div><div class="t m0 x3 h6 y5 ff1 fs2 fc0 sc0 ls0 ws0">致谢 xvi</div><div class="t m0 x3 h6 y6 ff1 fs2 fc0 sc0 ls0 ws0">网站 xxii</div><div class="t m0 x3 h6 y7 ff1 fs2 fc0 sc0 ls0 ws0">数学符号 xxiii</div><div class="t m0 x3 h6 y8 ff1 fs2 fc0 sc0 ls0 ws0">第一章 引言 1</div><div class="t m0 x4 h7 y9 ff4 fs2 fc0 sc0 ls0 ws0">1.1 本书面向的读者 . . . . . . . . . . . . . . . . . . . . . . . . . . 10</div><div class="t m0 x4 h7 ya ff4 fs2 fc0 sc0 ls0 ws0">1.2 深度学习的历史趋势 . . . . . . . . . . . . . . . . . . . . . . . 11</div><div class="t m0 x5 h7 yb ff4 fs2 fc0 sc0 ls0 ws0">1.2.1 神经网络的众多名称和命运变迁 . . . . . . . . . . . 12</div><div class="t m0 x5 h7 yc ff4 fs2 fc0 sc0 ls0 ws0">1.2.2 与日俱增的数据量 . . . . . . . . . . . . . . . . . . . 17</div><div class="t m0 x5 h7 yd ff4 fs2 fc0 sc0 ls0 ws0">1.2.3 与日俱增的模型规模 . . . . . . . . . . . . . . . . . . 19</div><div class="t m0 x5 h7 ye ff4 fs2 fc0 sc0 ls0 ws0">1.2.4 与日俱增的精度、复杂度和对现实世界的冲击 . . . . 22</div><div class="t m0 x3 h6 yf ff1 fs2 fc0 sc0 ls0 ws0">第一部分 应用数学与机器学习基础 25</div><div class="t m0 x3 h6 y10 ff1 fs2 fc0 sc0 ls0 ws0">第二章 线性代数 27</div><div class="t m0 x4 h7 y11 ff4 fs2 fc0 sc0 ls0 ws0">2.1 标量、向量、矩阵和张量 . . . . . . . . . . . . . . . . . . . . 27</div><div class="t m0 x4 h7 y12 ff4 fs2 fc0 sc0 ls0 ws0">2.2 矩阵和向量相乘 . . . . . . . . . . . . . . . . . . . . . . . . . . 29</div><div class="t m0 x4 h4 y13 ff4 fs2 fc0 sc0 ls0 ws0">2.3</div><div class="t m0 x5 h7 y14 ff3 fs2 fc0 sc0 ls0 ws0">单位矩阵和逆矩阵</div><div class="t m0 x6 h4 y13 ff4 fs2 fc0 sc0 ls0 ws0">. . . . . . . . . . . . . . . . . . . . . . . . 31</div><div class="t m0 x4 h7 y15 ff4 fs2 fc0 sc0 ls0 ws0">2.4 线性相关和生成子空间 . . . . . . . . . . . . . . . . . . . . . . 32</div><div class="t m0 x4 h7 y16 ff4 fs2 fc0 sc0 ls0 ws0">2.5 范数 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34</div><div class="t m0 x4 h7 y17 ff4 fs2 fc0 sc0 ls0 ws0">2.6 特殊类型的矩阵和向量 . . . . . . . . . . . . . . . . . . . . . . 36</div><div class="t m0 x4 h7 y18 ff4 fs2 fc0 sc0 ls0 ws0">2.7 特征分解 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37</div><div class="t m0 x7 h4 y19 ff4 fs2 fc0 sc0 ls0 ws0">iii</div><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a></div><div class="pi" data-data='{"ctm":[1.904762,0.000000,0.000000,1.904762,0.000000,0.000000]}'></div></div>

<div id="pf4" class="pf w0 h0" data-page-no="4"><div class="pc pc4 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/627a8cf45981aa38ef363dcd/bg4.jpg"><div class="t m0 x3 h7 y3 ff4 fs2 fc0 sc0 ls0 ws0">iv 目录</div><div class="t m0 x4 h7 y1a ff4 fs2 fc0 sc0 ls0 ws0">2.8 奇异值分解 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39</div><div class="t m0 x4 h7 y1b ff4 fs2 fc0 sc0 ls0 ws0">2.9 Moore-Penrose 伪逆 . . . . . . . . . . . . . . . . . . . . . . . 40</div><div class="t m0 x4 h7 y1c ff4 fs2 fc0 sc0 ls0 ws0">2.10 迹运算 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41</div><div class="t m0 x4 h7 y1d ff4 fs2 fc0 sc0 ls0 ws0">2.11 行列式 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42</div><div class="t m0 x4 h7 y1e ff4 fs2 fc0 sc0 ls0 ws0">2.12 实例：主成分分析 . . . . . . . . . . . . . . . . . . . . . . . . 42</div><div class="t m0 x3 h6 y1f ff1 fs2 fc0 sc0 ls0 ws0">第三章 概率与信息论 47</div><div class="t m0 x4 h7 y20 ff4 fs2 fc0 sc0 ls0 ws0">3.1 为什么要使用概率？ . . . . . . . . . . . . . . . . . . . . . . . 47</div><div class="t m0 x4 h7 y21 ff4 fs2 fc0 sc0 ls0 ws0">3.2 随机变量 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49</div><div class="t m0 x4 h7 y22 ff4 fs2 fc0 sc0 ls0 ws0">3.3 概率分布 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50</div><div class="t m0 x5 h7 y23 ff4 fs2 fc0 sc0 ls0 ws0">3.3.1 离散型变量和概率质量函数 . . . . . . . . . . . . . . 50</div><div class="t m0 x5 h7 y24 ff4 fs2 fc0 sc0 ls0 ws0">3.3.2 连续型变量和概率密度函数 . . . . . . . . . . . . . . 51</div><div class="t m0 x4 h7 y25 ff4 fs2 fc0 sc0 ls0 ws0">3.4 边缘概率 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52</div><div class="t m0 x4 h7 y26 ff4 fs2 fc0 sc0 ls0 ws0">3.5 条件概率 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52</div><div class="t m0 x4 h7 y27 ff4 fs2 fc0 sc0 ls0 ws0">3.6 条件概率的链式法则 . . . . . . . . . . . . . . . . . . . . . . . 53</div><div class="t m0 x4 h7 y28 ff4 fs2 fc0 sc0 ls0 ws0">3.7 独立性和条件独立性 . . . . . . . . . . . . . . . . . . . . . . . 53</div><div class="t m0 x4 h7 y29 ff4 fs2 fc0 sc0 ls0 ws0">3.8 期望、方差和协方差 . . . . . . . . . . . . . . . . . . . . . . . 54</div><div class="t m0 x4 h7 y2a ff4 fs2 fc0 sc0 ls0 ws0">3.9 常用概率分布 . . . . . . . . . . . . . . . . . . . . . . . . . . . 55</div><div class="t m0 x5 h7 y2b ff4 fs2 fc0 sc0 ls0 ws0">3.9.1 Bernoulli 分布 . . . . . . . . . . . . . . . . . . . . . 56</div><div class="t m0 x5 h7 y2c ff4 fs2 fc0 sc0 ls0 ws0">3.9.2 Multinoulli 分布 . . . . . . . . . . . . . . . . . . . . 56</div><div class="t m0 x5 h7 y2d ff4 fs2 fc0 sc0 ls0 ws0">3.9.3 高斯分布 . . . . . . . . . . . . . . . . . . . . . . . . 57</div><div class="t m0 x5 h7 y2e ff4 fs2 fc0 sc0 ls0 ws0">3.9.4 指数分布和 Laplace 分布 . . . . . . . . . . . . . . . 58</div><div class="t m0 x5 h7 y2f ff4 fs2 fc0 sc0 ls0 ws0">3.9.5 Dirac 分布和经验分布 . . . . . . . . . . . . . . . . . 59</div><div class="t m0 x5 h7 y30 ff4 fs2 fc0 sc0 ls0 ws0">3.9.6 分布的混合 . . . . . . . . . . . . . . . . . . . . . . . 59</div><div class="t m0 x4 h7 y31 ff4 fs2 fc0 sc0 ls0 ws0">3.10 常用函数的有用性质 . . . . . . . . . . . . . . . . . . . . . . . 61</div><div class="t m0 x4 h7 y32 ff4 fs2 fc0 sc0 ls0 ws0">3.11 贝叶斯规则 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63</div><div class="t m0 x4 h7 y33 ff4 fs2 fc0 sc0 ls0 ws0">3.12 连续型变量的技术细节 . . . . . . . . . . . . . . . . . . . . . . 64</div><div class="t m0 x4 h7 y34 ff4 fs2 fc0 sc0 ls0 ws0">3.13 信息论 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65</div><div class="t m0 x4 h7 y35 ff4 fs2 fc0 sc0 ls0 ws0">3.14 结构化概率模型 . . . . . . . . . . . . . . . . . . . . . . . . . . 69</div><div class="t m0 x3 h6 y36 ff1 fs2 fc0 sc0 ls0 ws0">第四章 数值计算 72</div><div class="t m0 x4 h7 y37 ff4 fs2 fc0 sc0 ls0 ws0">4.1 上溢和下溢 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72</div><div class="t m0 x4 h7 y18 ff4 fs2 fc0 sc0 ls0 ws0">4.2 病态条件 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73</div><a class="l" rel='nofollow' onclick='return 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<div id="pf5" class="pf w0 h0" data-page-no="5"><div class="pc pc5 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/627a8cf45981aa38ef363dcd/bg5.jpg"><div class="t m0 x3 h7 y3 ff6 fs2 fc0 sc0 ls0 ws0">目录 v</div><div class="t m0 x4 h7 y1a ff4 fs2 fc0 sc0 ls0 ws0">4.3 基于梯度的优化方法 . . . . . . . . . . . . . . . . . . . . . . . 74</div><div class="t m0 x5 h7 y38 ff4 fs2 fc0 sc0 ls0 ws0">4.3.1 梯度之上：Jacobian 和 Hessian 矩阵 . . . . . . . . . 77</div><div class="t m0 x4 h7 y39 ff4 fs2 fc0 sc0 ls0 ws0">4.4 约束优化 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82</div><div class="t m0 x4 h7 y3a ff4 fs2 fc0 sc0 ls0 ws0">4.5 实例：线性最小二乘 . . . . . . . . . . . . . . . . . . . . . . . 85</div><div class="t m0 x3 h6 y3b ff1 fs2 fc0 sc0 ls0 ws0">第五章 机器学习基础 87</div><div class="t m0 x4 h7 y3c ff4 fs2 fc0 sc0 ls0 ws0">5.1 学习算法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87</div><div class="t m0 x5 h7 y3d ff4 fs2 fc0 sc0 ls0 ws0">5.1.1 任务 T . . . . . . . . . . . . . . . . . . . . . . . . . 88</div><div class="t m0 x5 h7 y3e ff4 fs2 fc0 sc0 ls0 ws0">5.1.2 性能度量 P . . . . . . . . . . . . . . . . . . . . . . . 91</div><div class="t m0 x5 h7 y3f ff4 fs2 fc0 sc0 ls0 ws0">5.1.3 经验 E . . . . . . . . . . . . . . . . . . . . . . . . . 92</div><div class="t m0 x5 h7 y40 ff4 fs2 fc0 sc0 ls0 ws0">5.1.4 示例：线性回归 . . . . . . . . . . . . . . . . . . . . 94</div><div class="t m0 x4 h7 y41 ff4 fs2 fc0 sc0 ls0 ws0">5.2 容量、过拟合和欠拟合 . . . . . . . . . . . . . . . . . . . . . . 97</div><div class="t m0 x5 h7 y42 ff4 fs2 fc0 sc0 ls0 ws0">5.2.1 没有免费午餐定理 . . . . . . . . . . . . . . . . . . . 102</div><div class="t m0 x5 h7 y43 ff4 fs2 fc0 sc0 ls0 ws0">5.2.2 正则化 . . . . . . . . . . . . . . . . . . . . . . . . . . 104</div><div class="t m0 x4 h7 y44 ff4 fs2 fc0 sc0 ls0 ws0">5.3 超参数和验证集 . . . . . . . . . . . . . . . . . . . . . . . . . . 105</div><div class="t m0 x5 h7 y45 ff4 fs2 fc0 sc0 ls0 ws0">5.3.1 交叉验证 . . . . . . . . . . . . . . . . . . . . . . . . 106</div><div class="t m0 x4 h7 y46 ff4 fs2 fc0 sc0 ls0 ws0">5.4 估计、偏差和方差 . . . . . . . . . . . . . . . . . . . . . . . . 108</div><div class="t m0 x5 h7 y47 ff4 fs2 fc0 sc0 ls0 ws0">5.4.1 点估计 . . . . . . . . . . . . . . . . . . . . . . . . . . 108</div><div class="t m0 x5 h7 y48 ff4 fs2 fc0 sc0 ls0 ws0">5.4.2 偏差 . . . . . . . . . . . . . . . . . . . . . . . . . . . 109</div><div class="t m0 x5 h7 y49 ff4 fs2 fc0 sc0 ls0 ws0">5.4.3 方差和标准差 . . . . . . . . . . . . . . . . . . . . . . 111</div><div class="t m0 x5 h7 y4a ff4 fs2 fc0 sc0 ls0 ws0">5.4.4 权衡偏差和方差以最小化均方误差 . . . . . . . . . . 113</div><div class="t m0 x5 h7 y4b ff4 fs2 fc0 sc0 ls0 ws0">5.4.5 一致性 . . . . . . . . . . . . . . . . . . . . . . . . . . 114</div><div class="t m0 x4 h7 y4c ff4 fs2 fc0 sc0 ls0 ws0">5.5 最大似然估计 . . . . . . . . . . . . . . . . . . . . . . . . . . . 115</div><div class="t m0 x5 h7 y4d ff4 fs2 fc0 sc0 ls0 ws0">5.5.1 条件对数似然和均方误差 . . . . . . . . . . . . . . . 116</div><div class="t m0 x5 h7 y4e ff4 fs2 fc0 sc0 ls0 ws0">5.5.2 最大似然的性质 . . . . . . . . . . . . . . . . . . . . 117</div><div class="t m0 x4 h7 y4f ff4 fs2 fc0 sc0 ls0 ws0">5.6 贝叶斯统计 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118</div><div class="t m0 x5 h7 y50 ff4 fs2 fc0 sc0 ls0 ws0">5.6.1 最大后验 (MAP) 估计 . . . . . . . . . . . . . . . . . 121</div><div class="t m0 x4 h7 y51 ff4 fs2 fc0 sc0 ls0 ws0">5.7 监督学习算法 . . . . . . . . . . . . . . . . . . . . . . . . . . . 122</div><div class="t m0 x5 h7 y52 ff4 fs2 fc0 sc0 ls0 ws0">5.7.1 概率监督学习 . . . . . . . . . . . . . . . . . . . . . . 122</div><div class="t m0 x5 h7 y53 ff4 fs2 fc0 sc0 ls0 ws0">5.7.2 支持向量机 . . . . . . . . . . . . . . . . . . . . . . . 123</div><div class="t m0 x5 h7 y54 ff4 fs2 fc0 sc0 ls0 ws0">5.7.3 其他简单的监督学习算法 . . . . . . . . . . . . . . . 125</div><div class="t m0 x4 h7 y55 ff4 fs2 fc0 sc0 ls0 ws0">5.8 无监督学习算法 . . . . . . . . . . . . . . . . . . . . . . . . . . 128</div><div class="t m0 x5 h7 y18 ff4 fs2 fc0 sc0 ls0 ws0">5.8.1 主成分分析 . . . . . . . . . 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