《深度學習：原理與應用實踐.pdf》PDF高清完整版-免費下載

時間 2019-11-12

標籤深度學習原理應用實踐 pdf 高清完整免費下載简体版

原文原文鏈接

《深度學習：原理與應用實踐.pdf》PDF高清完整版-免費下載算法

《深度學習：原理與應用實踐.pdf》PDF高清完整版-免費下載數據庫

下載地址：網盤下載網絡

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本書全面、系統地介紹深度學習相關的技術，包括人工神經網絡，卷積神經網絡，深度學習平臺及源代碼分析，深度學習入門與進階，深度學習高級實踐，全部章節均附有源程序，全部實驗讀者都可重現，具備高度的可操做性和實用性。經過學習本書，研究人員、深度學習愛好者，可以在3 個月內，系統掌握深度學習相關的理論和技術。工具

目錄學習

深度學習基礎篇測試

第1 章緒論 ·································································································· 2字體

1.1 引言 ······································································································· 2orm

1.1.1 Google 的深度學習成果 ···························································· 2圖片

1.1.2 Microsoft 的深度學習成果························································· 3

1.1.3 國內公司的深度學習成果 ························································· 3

1.2 深度學習技術的發展歷程 ···································································· 4

1.3 深度學習的應用領域 ············································································ 6

1.3.1 圖像識別領域 ············································································· 6

1.3.2 語音識別領域 ············································································· 6

1.3.3 天然語言理解領域 ····································································· 7

1.4 如何開展深度學習的研究和應用開發 ················································· 7

本章參考文獻 ······························································································ 11

第2 章國內外深度學習技術研發現狀及其產業化趨勢 ······························· 13

2.1 Google 在深度學習領域的研發現狀 ·················································· 13

2.1.1 深度學習在Google 的應用 ······················································ 13

2.1.2 Google 的TensorFlow 深度學習平臺 ······································ 14

2.1.3 Google 的深度學習芯片TPU ·················································· 15

2.2 Facebook 在深度學習領域的研發現狀 ·············································· 15

2.2.1 Torch ···················································································· 15

2.2.2 DeepText ··················································································· 16

2.3 百度在深度學習領域的研發現狀 ······················································· 17

2.3.1 光學字符識別 ··········································································· 17

2.3.2 商品圖像搜索 ··········································································· 17

2.3.3 在線廣告 ·················································································· 18

2.3.4 以圖搜圖 ·················································································· 18

2.3.5 語音識別 ·················································································· 18

2.3.6 百度開源深度學習平臺MXNet 及其改進的深度語音識別系統Warp-CTC ····· 19

2.4 阿里巴巴在深度學習領域的研發現狀 ··············································· 19

2.4.1 拍立淘 ······················································································ 19

2.4.2 阿里小蜜——智能客服Messenger ········································· 20

2.5 京東在深度學習領域的研發現狀 ······················································· 20

2.6 騰訊在深度學習領域的研發現狀 ······················································· 21

2.7 科創型公司（基於深度學習的人臉識別系統） ······························· 22

2.8 深度學習的硬件支撐——NVIDIA GPU ············································ 23

本章參考文獻 ······························································································ 24

深度學習理論篇

第3 章神經網絡 ························································································· 30

3.1 神經元的概念 ······················································································ 30

3.2 神經網絡 ····························································································· 31

3.2.1 後向傳播算法 ··········································································· 32

3.2.2 後向傳播算法推導 ··································································· 33

3.3 神經網絡算法示例 ·············································································· 36

本章參考文獻 ······························································································ 38

第4 章卷積神經網絡 ················································································· 39

4.1 卷積神經網絡特性 ················································································ 39

4.1.1 局部鏈接 ·················································································· 40

4.1.2 權值共享 ·················································································· 41

4.1.3 空間相關下采樣 ······································································· 42

4.2 卷積神經網絡操做 ·············································································· 42

4.2.1 卷積操做 ·················································································· 42

4.2.2 下采樣操做 ·············································································· 44

4.3 卷積神經網絡示例：LeNet-5 ····························································· 45

本章參考文獻 ······························································································ 48

深度學習工具篇

第5 章深度學習工具Caffe ········································································ 50

5.1 Caffe 的安裝 ························································································ 50

5.1.1 安裝依賴包 ·············································································· 51

5.1.2 CUDA 安裝 ·············································································· 51

5.1.3 MATLAB 和Python 安裝 ························································ 54

5.1.4 OpenCV 安裝（可選） ···························································· 59

5.1.5 Intel MKL 或者BLAS 安裝 ····················································· 59

5.1.6 Caffe 編譯和測試 ····································································· 59

5.1.7 Caffe 安裝問題分析 ································································· 62

5.2 Caffe 框架與源代碼解析 ···································································· 63

5.2.1 數據層解析 ·············································································· 63

5.2.2 網絡層解析 ·············································································· 74

5.2.3 網絡結構解析 ··········································································· 92

5.2.4 網絡求解解析 ········································································· 104

本章參考文獻 ···························································································· 109

第6 章深度學習工具Pylearn2 ································································ 110

6.1 Pylearn2 的安裝 ·················································································· 110

6.1.1 相關依賴安裝 ·········································································· 110

6.1.2 安裝Pylearn2 ·········································································· 112

6.2 Pylearn2 的使用 ·················································································· 112

本章參考文獻 ····························································································· 116

深度學習實踐篇（入門與進階）

第7 章基於深度學習的手寫數字識別 ······················································ 118

7.1 數據介紹 ···························································································· 118

7.1.1 MNIST 數據集 ········································································ 118

7.1.2 提取MNIST 數據集圖片 ······················································· 120

7.2 手寫字體識別流程 ············································································ 121

7.2.1 模型介紹 ················································································ 121

7.2.2 操做流程 ················································································ 126

7.3 實驗結果分析 ···················································································· 127

本章參考文獻 ···························································································· 128

第8 章基於深度學習的圖像識別 ····························································· 129

8.1 數據來源 ··························································································· 129

8.1.1 Cifar10 數據集介紹 ································································ 129

8.1.2 Cifar10 數據集格式 ································································ 129

8.2 Cifar10 識別流程 ··············································································· 130

8.2.1 模型介紹 ················································································ 130

8.2.2 操做流程 ················································································ 136

8.3 實驗結果分析 ······················································································ 139

本章參考文獻 ···························································································· 140

第9 章基於深度學習的物體圖像識別 ······················································ 141

9.1 數據來源 ··························································································· 141

9.1.1 Caltech101 數據集 ·································································· 141

9.1.2 Caltech101 數據集處理 ·························································· 142

9.2 物體圖像識別流程 ············································································ 143

9.2.1 模型介紹 ················································································ 143

9.2.2 操做流程 ················································································ 144

9.3 實驗結果分析 ···················································································· 150

本章參考文獻 ···························································································· 151

第10 章基於深度學習的人臉識別 ··························································· 152

10.1 數據來源 ························································································· 152

10.1.1 AT＆T Facedatabase 數據庫 ·················································· 152

10.1.2 數據庫處理 ··········································································· 152

10.2 人臉識別流程 ·················································································· 154

10.2.1 模型介紹 ·············································································· 154

10.2.2 操做流程 ·············································································· 155

10.3 實驗結果分析 ·················································································· 159

本章參考文獻 ···························································································· 160

深度學習實踐篇（高級應用）

第11 章基於深度學習的人臉識別——DeepID 算法 ································ 162

11.1 問題定義與數據來源 ······································································ 162

11.2 算法原理 ·························································································· 163

11.2.1 數據預處理 ··········································································· 163

11.2.2 模型訓練策略 ······································································· 164

11.2.3 算法驗證和結果評估 ··························································· 164

11.3 人臉識別步驟 ·················································································· 165

11.3.1 數據預處理 ··········································································· 165

11.3.2 深度網絡結構模型 ······························································· 168

11.3.3 提取深度特徵與人臉驗證 ··················································· 171

11.4 實驗結果分析 ·················································································· 174

11.4.1 實驗數據 ··············································································· 174

11.4.2 實驗結果分析 ······································································· 175

本章參考文獻 ···························································································· 176

第12 章基於深度學習的表情識別 ··························································· 177

12.1 表情數據 ························································································· 177

12.1.1 Cohn-Kanade（CK+）數據庫 ············································· 177

12.1.2 JAFFE 數據庫 ······································································ 178

12.2 算法原理 ························································································· 179

12.3 表情識別步驟

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