深度學習:原理與應用實踐 深度学习:原理与应用实践
張重生
- 出版商: 電子工業
 - 出版日期: 2016-12-01
 - 定價: $288
 - 售價: 8.5 折 $245
 - 語言: 簡體中文
 - 頁數: 220
 - 裝訂: 平裝
 - ISBN: 7121304139
 - ISBN-13: 9787121304132
 - 
    相關分類:
    
      DeepLearning
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商品描述
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,捲積神經網絡,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,所有章節均附有源程序,所有實驗讀者均可重現,具有高度的可操作性和實用性。通過學習本書,研究人員、深度學習愛好者,能夠在3 個月內,系統掌握深度學習相關的理論和技術。
目錄大綱
深度學習基礎篇
第1章緒論········································· ·················································· ······· 2 
1.1引言········································ ·················································· ············· 2 
1.1.1 Google的深度學習成果···························· ································ 2 
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自然語言理解領域·················································· ··················· 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 Torchnet ································· ·················································· · 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阿裡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阿裡小蜜——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章捲積神經網絡··················· ·················································· ············ 39 
4.1捲積神經網絡特性······························· ················································· 39 
4.1.1局部連接············································· ····································· 40 
4.1.2權值共享······ ·················································· ·························· 41 
4.1.3空間相關下採樣················ ·················································· ····· 42 
4.2捲積神經網絡操作······································ ········································ 42 
4.2.1捲積操作··· ·················································· ····························· 42 
4.2.2下採樣操作·············· ·················································· ·············· 44 
4.3捲積神經網絡示例: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操作流程···························· ·················································· ·· 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操作流程··························· ·················································· ··· 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操作流程····································· ··········································· 144 
9.3實驗結果分析·· ·················································· ··········
