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├── .github
    └── ISSUE_TEMPLATE
    │   ├── bug_report.md
    │   └── feature_request.md
├── .gitignore
├── .nojekyll
├── 404.html
├── Dockerfile
├── LICENSE
├── NAV.md
├── README.md
├── SUMMARY.md
├── asset
    ├── back-to-top.css
    ├── back-to-top.js
    ├── dark-mode.css
    ├── dark-mode.js
    ├── docsify-apachecn-footer.js
    ├── docsify-baidu-push.js
    ├── docsify-baidu-stat.js
    ├── docsify-clicker.js
    ├── docsify-cnzz.js
    ├── docsify-copy-code.min.js
    ├── docsify-katex.js
    ├── docsify-quick-page.css
    ├── docsify-quick-page.js
    ├── docsify-sidebar-collapse.min.js
    ├── docsify.min.js
    ├── edit.css
    ├── edit.js
    ├── edit.svg
    ├── fonts
    │   ├── KaTeX_AMS-Regular.ttf
    │   ├── KaTeX_AMS-Regular.woff
    │   ├── KaTeX_AMS-Regular.woff2
    │   ├── KaTeX_Caligraphic-Bold.ttf
    │   ├── KaTeX_Caligraphic-Bold.woff
    │   ├── KaTeX_Caligraphic-Bold.woff2
    │   ├── KaTeX_Caligraphic-Regular.ttf
    │   ├── KaTeX_Caligraphic-Regular.woff
    │   ├── KaTeX_Caligraphic-Regular.woff2
    │   ├── KaTeX_Fraktur-Bold.ttf
    │   ├── KaTeX_Fraktur-Bold.woff
    │   ├── KaTeX_Fraktur-Bold.woff2
    │   ├── KaTeX_Fraktur-Regular.ttf
    │   ├── KaTeX_Fraktur-Regular.woff
    │   ├── KaTeX_Fraktur-Regular.woff2
    │   ├── KaTeX_Main-Bold.ttf
    │   ├── KaTeX_Main-Bold.woff
    │   ├── KaTeX_Main-Bold.woff2
    │   ├── KaTeX_Main-BoldItalic.ttf
    │   ├── KaTeX_Main-BoldItalic.woff
    │   ├── KaTeX_Main-BoldItalic.woff2
    │   ├── KaTeX_Main-Italic.ttf
    │   ├── KaTeX_Main-Italic.woff
    │   ├── KaTeX_Main-Italic.woff2
    │   ├── KaTeX_Main-Regular.ttf
    │   ├── KaTeX_Main-Regular.woff
    │   ├── KaTeX_Main-Regular.woff2
    │   ├── KaTeX_Math-BoldItalic.ttf
    │   ├── KaTeX_Math-BoldItalic.woff
    │   ├── KaTeX_Math-BoldItalic.woff2
    │   ├── KaTeX_Math-Italic.ttf
    │   ├── KaTeX_Math-Italic.woff
    │   ├── KaTeX_Math-Italic.woff2
    │   ├── KaTeX_SansSerif-Bold.ttf
    │   ├── KaTeX_SansSerif-Bold.woff
    │   ├── KaTeX_SansSerif-Bold.woff2
    │   ├── KaTeX_SansSerif-Italic.ttf
    │   ├── KaTeX_SansSerif-Italic.woff
    │   ├── KaTeX_SansSerif-Italic.woff2
    │   ├── KaTeX_SansSerif-Regular.ttf
    │   ├── KaTeX_SansSerif-Regular.woff
    │   ├── KaTeX_SansSerif-Regular.woff2
    │   ├── KaTeX_Script-Regular.ttf
    │   ├── KaTeX_Script-Regular.woff
    │   ├── KaTeX_Script-Regular.woff2
    │   ├── KaTeX_Size1-Regular.ttf
    │   ├── KaTeX_Size1-Regular.woff
    │   ├── KaTeX_Size1-Regular.woff2
    │   ├── KaTeX_Size2-Regular.ttf
    │   ├── KaTeX_Size2-Regular.woff
    │   ├── KaTeX_Size2-Regular.woff2
    │   ├── KaTeX_Size3-Regular.ttf
    │   ├── KaTeX_Size3-Regular.woff
    │   ├── KaTeX_Size3-Regular.woff2
    │   ├── KaTeX_Size4-Regular.ttf
    │   ├── KaTeX_Size4-Regular.woff
    │   ├── KaTeX_Size4-Regular.woff2
    │   ├── KaTeX_Typewriter-Regular.ttf
    │   ├── KaTeX_Typewriter-Regular.woff
    │   └── KaTeX_Typewriter-Regular.woff2
    ├── katex.min.css
    ├── left.svg
    ├── moon.svg
    ├── prism-c.min.js
    ├── prism-cpp.min.js
    ├── prism-csharp.min.js
    ├── prism-darcula.css
    ├── prism-java.min.js
    ├── prism-javascript.min.js
    ├── prism-php.min.js
    ├── prism-python.min.js
    ├── right.svg
    ├── search.min.js
    ├── share.css
    ├── share.js
    ├── share.svg
    ├── sidebar.min.css
    ├── style.css
    ├── sun.svg
    ├── up.svg
    └── vue.css
├── docs
    ├── contrib.md
    ├── da
    │   ├── 001.md
    │   ├── 002.md
    │   ├── 003.md
    │   ├── 004.md
    │   ├── 005.md
    │   ├── 006.md
    │   ├── 007.md
    │   ├── 008.md
    │   ├── 009.md
    │   ├── 010.md
    │   ├── 011.md
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    │   ├── 015.md
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    │   ├── 047.md
    │   ├── 048.md
    │   ├── 049.md
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    │   ├── 055.md
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    │   ├── 064.md
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    │   ├── 073.md
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    │   ├── 080.md
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    │   ├── 090.md
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    │   ├── 094.md
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    │   ├── 100.md
    │   ├── 101.md
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    │   ├── 140.md
    │   ├── 141.md
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    │   ├── 143.md
    │   ├── 144.md
    │   ├── 145.md
    │   ├── 146.md
    │   ├── 147.md
    │   ├── 148.md
    │   ├── 149.md
    │   ├── 150.md
    │   ├── 151.md
    │   ├── 152.md
    │   ├── 153.md
    │   ├── README.md
    │   ├── SUMMARY.md
    │   └── img
    │   │   ├── 2034209be09abc075fb9354140bbca18.jpg
    │   │   ├── 711435337d08bbac7eb35b946af5b970.jpg
    │   │   └── ba74cf5bc8ea89099c03b3d738f92cf1.jpg
    ├── faq
    │   ├── 1.机器学习实战-复习版.md
    │   ├── img
    │   │   └── faq_1.png
    │   └── 直播问题汇总.md
    ├── img
    │   ├── ApacheCM-ML-WangYiYunKeTang.png
    │   ├── ApacheCM-ML-youku.jpg
    │   ├── ApacheCN-ML-AcFun.jpg
    │   ├── ApacheCN-ML-bilibili-compare.jpg
    │   ├── ApacheCN-ML-bilibili.jpg
    │   ├── ApacheCN-group.png
    │   └── logo.jpg
    ├── linalg
    │   ├── README.md
    │   ├── SUMMARY.md
    │   ├── chapter01.md
    │   ├── chapter02.md
    │   ├── chapter03.md
    │   ├── chapter04.md
    │   ├── chapter05.md
    │   ├── chapter06.md
    │   ├── chapter07.md
    │   ├── chapter08.md
    │   ├── chapter09.md
    │   ├── chapter10.md
    │   ├── chapter11.md
    │   ├── chapter12.md
    │   ├── chapter13.md
    │   ├── chapter14.md
    │   ├── chapter15.md
    │   ├── chapter16.md
    │   ├── chapter17.md
    │   ├── chapter18.md
    │   ├── chapter19.md
    │   ├── chapter20.md
    │   ├── chapter21.md
    │   ├── chapter22.md
    │   ├── chapter23.md
    │   ├── chapter24.md
    │   ├── chapter25.md
    │   ├── chapter26.md
    │   ├── chapter27.md
    │   ├── chapter28.md
    │   ├── chapter29.md
    │   ├── chapter30.md
    │   ├── chapter31.md
    │   ├── chapter32.md
    │   ├── chapter33.md
    │   ├── chapter34.md
    │   ├── chapter35.md
    │   └── img
    │   │   ├── chapter01_1_0.png
    │   │   ├── chapter01_4_0.png
    │   │   ├── chapter12_1_0.png
    │   │   ├── chapter12_3_0.png
    │   │   ├── chapter15_1_0.png
    │   │   ├── chapter15_4_0.png
    │   │   ├── chapter16_1_0.png
    │   │   ├── chapter31_1_0.png
    │   │   ├── chapter31_4_0.png
    │   │   ├── chapter35_1_0.png
    │   │   ├── graph_12.png
    │   │   ├── graph_15_1.png
    │   │   ├── graph_15_2.png
    │   │   └── graph_16_1.png
    ├── misc
    │   ├── AI学习路线.md
    │   ├── AI常用函数说明.md
    │   ├── CNN原理.md
    │   ├── LSTM原理.md
    │   ├── RNN原理.md
    │   ├── contributor.md
    │   ├── img
    │   │   ├── CNN原理
    │   │   │   ├── 853467-20171031123650574-11330636.png
    │   │   │   ├── 853467-20171031215017701-495180034.png
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    │   │   │   └── 853467-20171104142200763-1912037434.png
    │   │   ├── LSTM原理
    │   │   │   ├── 20180704173230785.jpg
    │   │   │   ├── 20180704173253439.jpg
    │   │   │   ├── 20180705152515679.jpg
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    │   │   │   ├── 20180705164102617.jpg
    │   │   │   ├── 20180713200802779.jpg
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    │   │   │   ├── 20180713210738834.jpg
    │   │   │   └── 20180713211322965.jpg
    │   │   ├── RNN原理
    │   │   │   ├── 15570321772488.jpg
    │   │   │   ├── 15570322195709.jpg
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    │   │   │   ├── 20171119130251741.jpg
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    │   │   │   ├── 20171221152506461.jpg
    │   │   │   ├── bi-directional-rnn.png
    │   │   │   ├── deep-bi-directional-rnn-classification.png
    │   │   │   ├── deep-bi-directional-rnn-hidden-layer.png
    │   │   │   └── deep-bi-directional-rnn.png
    │   │   └── 反向传递
    │   │   │   ├── 853467-20160630140644406-409859737.png
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    │   │   │   └── 853467-20160630160603484-1471434475.png
    │   ├── linear-logistic-mle.md
    │   ├── naive-bayes-discuss.md
    │   ├── why-to-record-study-ml-video.md
    │   └── 反向传递.md
    ├── ml
    │   ├── 1.md
    │   ├── 10.md
    │   ├── 11.md
    │   ├── 12.md
    │   ├── 13.md
    │   ├── 14.md
    │   ├── 15.md
    │   ├── 16.md
    │   ├── 2.md
    │   ├── 3.md
    │   ├── 4.md
    │   ├── 5.md
    │   ├── 6.1.md
    │   ├── 6.md
    │   ├── 7.md
    │   ├── 8.md
    │   ├── 9.md
    │   ├── README.md
    │   └── img
    │   │   ├── Apriori流程图.png
    │   │   ├── CART构建数据集回归树的简单数据集.png
    │   │   ├── DT_海洋生物数据.png
    │   │   ├── DecisionTree_headPage_xy.png
    │   │   ├── DecisionTree_headpage.jpg
    │   │   ├── GUI更好的示例图.png
    │   │   ├── GUI示例图.png
    │   │   ├── K-Means_首页.jpg
    │   │   ├── LR_1.png
    │   │   ├── LR_10.png
    │   │   ├── LR_11.png
    │   │   ├── LR_12.png
    │   │   ├── LR_13.png
    │   │   ├── LR_14.png
    │   │   ├── LR_15.png
    │   │   ├── LR_16.png
    │   │   ├── LR_17.png
    │   │   ├── LR_18.png
    │   │   ├── LR_19.png
    │   │   ├── LR_2.png
    │   │   ├── LR_20.png
    │   │   ├── LR_21.png
    │   │   ├── LR_3.png
    │   │   ├── LR_4.png
    │   │   ├── LR_5.png
    │   │   ├── LR_6.png
    │   │   ├── LR_7.png
    │   │   ├── LR_8.png
    │   │   ├── LR_9.png
    │   │   ├── LinearR_1.png
    │   │   ├── LinearR_10.png
    │   │   ├── LinearR_11.png
    │   │   ├── LinearR_12.png
    │   │   ├── LinearR_13.png
    │   │   ├── LinearR_14.png
    │   │   ├── LinearR_15.png
    │   │   ├── LinearR_16.png
    │   │   ├── LinearR_17.png
    │   │   ├── LinearR_18.png
    │   │   ├── LinearR_19.png
    │   │   ├── LinearR_2.png
    │   │   ├── LinearR_20.png
    │   │   ├── LinearR_21.png
    │   │   ├── LinearR_22.png
    │   │   ├── LinearR_23.png
    │   │   ├── LinearR_3.png
    │   │   ├── LinearR_4.png
    │   │   ├── LinearR_5.png
    │   │   ├── LinearR_6.png
    │   │   ├── LinearR_7.png
    │   │   ├── LinearR_8.png
    │   │   ├── LinearR_9.png
    │   │   ├── LogisticRegression_headPage_xy.png
    │   │   ├── Logistic回归Sigmoid函数.png
    │   │   ├── Logistic回归首页.png
    │   │   ├── Matplotlib绘制树形图.png
    │   │   ├── NB_2.png
    │   │   ├── NB_3.png
    │   │   ├── NB_4.png
    │   │   ├── NB_5.png
    │   │   ├── NB_6.png
    │   │   ├── NB_7.png
    │   │   ├── NavieBayesian_headPage_xy.png
    │   │   ├── PCA分析数据过程.jpg
    │   │   ├── ROC曲线.png
    │   │   ├── RegTree_1.png
    │   │   ├── RegTree_2.png
    │   │   ├── RegTree_3.png
    │   │   ├── RegTree_4.png
    │   │   ├── RegTree_5.png
    │   │   ├── SVD_推荐系统_主题空间案例1.jpg
    │   │   ├── SVD公式的测试案例.jpg
    │   │   ├── SVM_1.jpg
    │   │   ├── SVM_2_separating-hyperplane.jpg
    │   │   ├── SVM_3_linearly-separable.jpg
    │   │   ├── SVM_4_point2line-distance.jpg
    │   │   ├── SVM_4_point2line-distance.png
    │   │   ├── SVM_5_Lagrangemultiplier.png
    │   │   ├── SVM_6_radial-basis-function.jpg
    │   │   ├── SVM_松弛变量.jpg
    │   │   ├── Thumbs.db
    │   │   ├── TreeRegression_headPage_xy.png
    │   │   ├── adaboost_alpha.png
    │   │   ├── adaboost_code-flow-chart.jpg
    │   │   ├── adaboost_headPage.jpg
    │   │   ├── adaboost_illustration.png
    │   │   ├── alpha.png
    │   │   ├── apachecn-bikmeans-run-result-1.jpg
    │   │   ├── apachecn-k-means-run-result-1.jpg
    │   │   ├── apachecn-k-means-term-1.jpg
    │   │   ├── apachecn-kmeans-partial-best-result-1.jpg
    │   │   ├── apachecn_apriori_association_demo_1.jpg
    │   │   ├── apachecn_apriori_goods_all_1.jpg
    │   │   ├── apachecn_apriori_homepage.jpg
    │   │   ├── apachecn_apriori_not_frequent_item_sets_demo_1.jpg
    │   │   ├── apachecn_association_rule_demo_1.jpg
    │   │   ├── apachecn_fp_growth_homepage.png
    │   │   ├── arctan_arccot.gif
    │   │   ├── b.png
    │   │   ├── hu_1.jpg
    │   │   ├── hu_10.png
    │   │   ├── hu_2.jpg
    │   │   ├── hu_3.png
    │   │   ├── hu_4.png
    │   │   ├── hu_5.png
    │   │   ├── hu_6.png
    │   │   ├── hu_7.png
    │   │   ├── hu_8.png
    │   │   ├── hu_9.png
    │   │   ├── k_1.jpg
    │   │   ├── k_10.png
    │   │   ├── k_11.png
    │   │   ├── k_12.png
    │   │   ├── k_13.png
    │   │   ├── k_14.png
    │   │   ├── k_15.png
    │   │   ├── k_16.png
    │   │   ├── k_2.jpg
    │   │   ├── k_3.jpg
    │   │   ├── k_4.jpg
    │   │   ├── k_5.jpg
    │   │   ├── k_6.png
    │   │   ├── k_7.png
    │   │   ├── k_8.png
    │   │   ├── k_9.png
    │   │   ├── knn-0-headpage.jpg
    │   │   ├── knn-1-movie.png
    │   │   ├── knn_1.png
    │   │   ├── knn_2.jpg
    │   │   ├── knn_2_handWriting.png
    │   │   ├── knn_3.png
    │   │   ├── knn_4.png
    │   │   ├── knn_headPage_xy.png
    │   │   ├── knn_later_1.png
    │   │   ├── knn_later_2.png
    │   │   ├── knn_later_3.png
    │   │   ├── knn_later_4.png
    │   │   ├── knn_matplotlib_2.png
    │   │   ├── ml_add_1.jpg
    │   │   ├── ml_add_2.jpg
    │   │   ├── ml_algorithm.jpg
    │   │   ├── ml_map.png
    │   │   ├── mr_1_cluster.jpg
    │   │   ├── mr_headPage.jpg
    │   │   ├── story_1.png
    │   │   ├── story_2.png
    │   │   ├── story_3.png
    │   │   ├── story_4.png
    │   │   ├── story_5.png
    │   │   ├── story_6.png
    │   │   ├── story_7.png
    │   │   ├── story_8.png
    │   │   ├── supportVector.png
    │   │   ├── supportVector公式.jpg
    │   │   ├── svd_headPage.jpg
    │   │   ├── svm_2.png
    │   │   ├── w.png
    │   │   ├── 交易清单.png
    │   │   ├── 代价函数.png
    │   │   ├── 使用SVD简化数据-LSI举例.png
    │   │   ├── 使用SVD简化数据-SVD公式.jpg
    │   │   ├── 使用SVD简化数据-基于物品相似度.png
    │   │   ├── 使用SVD简化数据-基于用户相似度.png
    │   │   ├── 决策树-流程图.jpg
    │   │   ├── 决策树划分数据集时的数据路径.png
    │   │   ├── 决策树流程介绍图.jpg
    │   │   ├── 利用PCA简化数据_首页.jpg
    │   │   ├── 基于SVD.png
    │   │   ├── 基于物品相似度.jpg
    │   │   ├── 基于知识的推荐.jpg
    │   │   ├── 局部加权线性回归效果图.png
    │   │   ├── 岭回归示例图.png
    │   │   ├── 应用PCA降维.png
    │   │   ├── 所有可能的项集组合.png
    │   │   ├── 拟合程度示例图.png
    │   │   ├── 拟合程度较好示例图.png
    │   │   ├── 推荐方法对比.png
    │   │   ├── 数据重抽样.jpg
    │   │   ├── 方向导数和梯度.png
    │   │   ├── 朴素贝叶斯_首页.png
    │   │   ├── 朴素贝叶斯示例数据分布.png
    │   │   ├── 机器学习基础-选择算法.jpg
    │   │   ├── 机器学习基础-首页.jpg
    │   │   ├── 机器学习基础训练过程.jpg
    │   │   ├── 松弛变量.png
    │   │   ├── 树回归首页.png
    │   │   ├── 梯度上升算法.png
    │   │   ├── 模型树示例图.png
    │   │   ├── 欠拟合示例图.png
    │   │   ├── 欧式距离的计算方式.jpg
    │   │   ├── 步骤1-3.png
    │   │   ├── 步骤4-5.png
    │   │   ├── 步骤6-1.png
    │   │   ├── 步骤6-2.png
    │   │   ├── 步骤7-1.png
    │   │   ├── 步骤7-2.png
    │   │   ├── 测试回归树的分段常数数据集.png
    │   │   ├── 熵的计算公式.jpg
    │   │   ├── 特征重抽样.jpg
    │   │   ├── 第十一章--Apriori算法进行关联分析.xlsx
    │   │   ├── 线性回归效果图.png
    │   │   ├── 贝叶斯条件概率.png
    │   │   ├── 过拟合.png
    │   │   ├── 过拟合图解.png
    │   │   ├── 过拟合示例图.png
    │   │   ├── 逐步线性回归示例图.png
    │   │   ├── 非频繁项集.png
    │   │   ├── 项目数据导入.jpg
    │   │   └── 预测数值型数据回归首页.png
    ├── nlp
    │   ├── 0.md
    │   ├── 1.md
    │   ├── 10.md
    │   ├── 11.md
    │   ├── 12.md
    │   ├── 14.md
    │   ├── 2.md
    │   ├── 3.md
    │   ├── 4.md
    │   ├── 5.md
    │   ├── 6.md
    │   ├── 7.md
    │   ├── 8.md
    │   ├── 9.md
    │   ├── Images
    │   │   ├── 05c7618d4554f83cfa6105c528703794.jpg
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    │   │   ├── f4891d12ae20c39b685951ad3cddf1aa.jpg
    │   │   ├── f9e1ba3246770e3ecb24f813f33f2075.jpg
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    │   │   └── fff90c564d2625f739b442b23301906e.jpg
    │   ├── README.md
    │   └── SUMMARY.md
    ├── nlp_old
    │   ├── 1.入门介绍.md
    │   ├── 2.分词.md
    │   ├── 3.1.篇章分析-内容概述.md
    │   ├── 3.2.篇章分析-内容标签.md
    │   ├── 3.3.篇章分析-情感分析.md
    │   ├── 3.4.篇章分析-自动摘要.md
    │   ├── 3.命名实体识别.md
    │   ├── README.md
    │   ├── Word2Vec.md
    │   └── img
    │   │   ├── 1.自然语言处理入门介绍
    │   │       ├── 机器翻译.png
    │   │       └── 篇章分析.jpg
    │   │   ├── 3.1.篇章分析-内容标签
    │   │       └── 篇章分析任务.jpg
    │   │   ├── 3.2.篇章分析-内容标签
    │   │       ├── 主题分类.jpg
    │   │       ├── 内容标签在Feed流中的应用.jpg
    │   │       ├── 基于大数据分析的图谱构建.jpg
    │   │       ├── 百度内容标签.jpg
    │   │       ├── 通用标签.jpg
    │   │       └── 面向推荐的标签图谱.jpg
    │   │   ├── 3.3.篇章分析-情感分类
    │   │       ├── 情感分类.jpg
    │   │       ├── 情感分类和观点挖掘.jpg
    │   │       ├── 百度应用推荐理由.jpg
    │   │       ├── 百度应用评论观点.jpg
    │   │       ├── 观点挖掘.jpg
    │   │       └── 观点摘要.jpg
    │   │   ├── 3.4.篇章分析-自动摘要
    │   │       ├── 信息爆炸与移动化.jpg
    │   │       ├── 典型摘要计算流程.jpg
    │   │       ├── 基于篇章信息的通用新闻摘要.jpg
    │   │       ├── 总结.jpg
    │   │       ├── 摘要系统.jpg
    │   │       ├── 百度应用搜索播报摘要和图像摘要.jpg
    │   │       ├── 百度应用文本和语言摘要.jpg
    │   │       ├── 百度应用问答摘要.jpg
    │   │       ├── 篇章主题摘要.jpg
    │   │       ├── 自动摘要分类.jpg
    │   │       └── 问答摘要.jpg
    │   │   ├── F94581F64C21A1094A473397DFA42F9C.jpg
    │   │   └── Word2Vce
    │   │       ├── CBoW.png
    │   │       └── Skip-gram.png
    ├── old_README.md
    ├── pytorch
    │   ├── 01.md
    │   ├── 02.md
    │   ├── 03.md
    │   ├── 04.md
    │   ├── 05.md
    │   ├── 06.md
    │   ├── 07.md
    │   ├── 08.md
    │   ├── 09.md
    │   ├── 10.md
    │   ├── 11.md
    │   ├── 12.md
    │   ├── 13.md
    │   ├── 14.md
    │   ├── 15.md
    │   ├── 16.md
    │   ├── 17.md
    │   ├── 18.md
    │   ├── 19.md
    │   ├── 20.md
    │   ├── 21.md
    │   ├── 22.md
    │   ├── 23.md
    │   ├── 24.md
    │   ├── 25.md
    │   ├── 26.md
    │   ├── README.md
    │   ├── SUMMARY.md
    │   └── img
    │   │   ├── 03f4667f9aae4918338a56b74865a389.png
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    ├── report
    │   ├── 2017-04-08.md
    │   └── img
    │   │   ├── 2017-04-08_第一期的总结_1.jpg
    │   │   ├── 2017-04-08_第一期的总结_10.jpg
    │   │   ├── 2017-04-08_第一期的总结_11.jpg
    │   │   ├── 2017-04-08_第一期的总结_12.jpg
    │   │   ├── 2017-04-08_第一期的总结_2.jpg
    │   │   ├── 2017-04-08_第一期的总结_3.jpg
    │   │   ├── 2017-04-08_第一期的总结_4.jpg
    │   │   ├── 2017-04-08_第一期的总结_5.jpg
    │   │   ├── 2017-04-08_第一期的总结_6.jpg
    │   │   ├── 2017-04-08_第一期的总结_7.jpg
    │   │   ├── 2017-04-08_第一期的总结_8.jpg
    │   │   └── 2017-04-08_第一期的总结_9.jpg
    └── tf2
    │   ├── 10.md
    │   ├── 11.md
    │   ├── 12.md
    │   ├── 13.md
    │   ├── 14.md
    │   ├── 15.md
    │   ├── 16.md
    │   ├── 17.md
    │   ├── 18.md
    │   ├── 19.md
    │   ├── README.md
    │   ├── SUMMARY.md
    │   └── img
    │       ├── 0206020c7e2549b82019ce1da567f097.png
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    │       ├── tex-ffe9f913124f345732e9f00fa258552e.gif
    │       ├── 图4-1.PNG
    │       ├── 图4-10.PNG
    │       ├── 图4-11.PNG
    │       ├── 图4-12.PNG
    │       ├── 图4-13.PNG
    │       ├── 图4-14.PNG
    │       ├── 图4-15.PNG
    │       ├── 图4-16.PNG
    │       ├── 图4-17.PNG
    │       ├── 图4-18.PNG
    │       ├── 图4-19.PNG
    │       ├── 图4-2.PNG
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    │       ├── 图4-9.PNG
    │       └── 表4-1.PNG
├── img
    └── ad
    │   └── partnerstack.gif
├── index.html
├── old
    ├── SECURITY.md
    ├── ads.txt
    ├── book.json
    ├── requirements.txt
    ├── run_example.py
    └── run_website.sh
├── run_example.py
├── src
    ├── config
    │   ├── __init__.py
    │   └── setting.py
    ├── py2.x
    │   ├── dl
    │   │   ├── activators.py
    │   │   ├── bp.py
    │   │   ├── cnn.py
    │   │   ├── fc.py
    │   │   ├── linear_unit.py
    │   │   ├── lstm.py
    │   │   ├── mnist.py
    │   │   ├── perceptron.py
    │   │   ├── recursive.py
    │   │   └── rnn.py
    │   └── ml
    │   │   ├── 1.MLFoundation
    │   │       └── NumPy.py
    │   │   ├── 10.kmeans
    │   │       ├── kMeans.py
    │   │       ├── kMeansSklearn.py
    │   │       └── test.txt
    │   │   ├── 11.Apriori
    │   │       └── apriori.py
    │   │   ├── 12.FrequentPattemTree
    │   │       └── fpGrowth.py
    │   │   ├── 13.PCA
    │   │       └── pca.py
    │   │   ├── 14.SVD
    │   │       └── svdRecommend.py
    │   │   ├── 15.BigData_MapReduce
    │   │       ├── mrMean.py
    │   │       ├── mrMeanMapper.py
    │   │       ├── mrMeanReducer.py
    │   │       ├── mrSVM.py
    │   │       ├── mrSVMkickStart.py
    │   │       ├── pegasos.py
    │   │       ├── proximalSVM.py
    │   │       ├── py27dbg.py
    │   │       └── wc.py
    │   │   ├── 2.KNN
    │   │       ├── kNN.py
    │   │       └── sklearn-knn-demo.py
    │   │   ├── 3.DecisionTree
    │   │       ├── DTSklearn.py
    │   │       ├── DecisionTree.py
    │   │       ├── decisionTreePlot.py
    │   │       ├── skelearn_dts_regressor_demo.py
    │   │       └── sklearn_dts_classify_demo.py
    │   │   ├── 4.NaiveBayes
    │   │       ├── bayes.py
    │   │       └── sklearn-nb-demo.py
    │   │   ├── 5.Logistic
    │   │       ├── logistic.py
    │   │       └── sklearn_logisticRegression_demo.py
    │   │   ├── 6.SVM
    │   │       ├── sklearn-svm-demo.py
    │   │       ├── svm-complete.py
    │   │       ├── svm-complete_Non-Kernel.py
    │   │       └── svm-simple.py
    │   │   ├── 7.AdaBoost
    │   │       ├── adaboost.py
    │   │       └── sklearn-adaboost-demo.py
    │   │   ├── 7.RandomForest
    │   │       └── randomForest.py
    │   │   ├── 8.Regression
    │   │       ├── regression.py
    │   │       └── sklearn-regression-demo.py
    │   │   └── 9.RegTrees
    │   │       ├── RTSklearn.py
    │   │       ├── regTrees.py
    │   │       ├── sklearn-regressTree-demo.py
    │   │       └── treeExplore.py
    ├── py3.x
    │   ├── dl
    │   │   ├── activators.py
    │   │   ├── bp.py
    │   │   ├── cnn.py
    │   │   ├── fc.py
    │   │   ├── linear_unit.py
    │   │   ├── lstm.py
    │   │   ├── mnist.py
    │   │   ├── perceptron.py
    │   │   ├── recursive.py
    │   │   └── rnn.py
    │   ├── ml
    │   │   ├── 1.MLFoundation
    │   │   │   └── NumPy.py
    │   │   ├── 10.kmeans
    │   │   │   ├── __init__.py
    │   │   │   ├── k-means.md
    │   │   │   ├── kMeans.py
    │   │   │   ├── kMeansSklearn.py
    │   │   │   └── test.txt
    │   │   ├── 11.Apriori
    │   │   │   └── apriori.py
    │   │   ├── 12.FrequentPattemTree
    │   │   │   └── fpGrowth.py
    │   │   ├── 13.PCA
    │   │   │   └── pca.py
    │   │   ├── 14.SVD
    │   │   │   └── svdRecommend.py
    │   │   ├── 15.BigData_MapReduce
    │   │   │   ├── mrMean.py
    │   │   │   ├── mrMeanMapper.py
    │   │   │   ├── mrMeanReducer.py
    │   │   │   ├── mrSVM.py
    │   │   │   ├── mrSVMkickStart.py
    │   │   │   ├── pegasos.py
    │   │   │   ├── proximalSVM.py
    │   │   │   ├── py27dbg.py
    │   │   │   └── wc.py
    │   │   ├── 16.RecommenderSystems
    │   │   │   ├── RS-itemcf.py
    │   │   │   ├── RS-usercf.py
    │   │   │   ├── python
    │   │   │   │   └── Recommender.py
    │   │   │   ├── sklearn-RS-demo-cf-item-test.py
    │   │   │   ├── sklearn-RS-demo-item.py
    │   │   │   ├── sklearn-RS-demo-user.py
    │   │   │   ├── sklearn-RS-demo.py
    │   │   │   ├── test_evaluation_model.py
    │   │   │   ├── test_graph-based.py
    │   │   │   ├── test_lfm.py
    │   │   │   ├── test_基于物品.py
    │   │   │   └── test_基于用户.py
    │   │   ├── 2.KNN
    │   │   │   ├── kNN.py
    │   │   │   └── sklearn-knn-demo.py
    │   │   ├── 3.DecisionTree
    │   │   │   ├── DTSklearn.py
    │   │   │   ├── DecisionTree.py
    │   │   │   ├── decisionTreePlot.py
    │   │   │   ├── skelearn_dts_regressor_demo.py
    │   │   │   └── sklearn_dts_classify_demo.py
    │   │   ├── 4.NaiveBayes
    │   │   │   ├── bayes.py
    │   │   │   └── sklearn-nb-demo.py
    │   │   ├── 5.Logistic
    │   │   │   ├── logistic.py
    │   │   │   └── sklearn_logisticRegression_demo.py
    │   │   ├── 6.SVM
    │   │   │   ├── sklearn-svm-demo.py
    │   │   │   ├── svm-complete.py
    │   │   │   ├── svm-complete_Non-Kernel.py
    │   │   │   └── svm-simple.py
    │   │   ├── 7.AdaBoost
    │   │   │   ├── adaboost.py
    │   │   │   ├── roc_test.py
    │   │   │   └── sklearn-adaboost-demo.py
    │   │   ├── 7.RandomForest
    │   │   │   └── randomForest.py
    │   │   ├── 8.Regression
    │   │   │   ├── regression.py
    │   │   │   └── sklearn-regression-demo.py
    │   │   └── 9.RegTrees
    │   │   │   ├── RTSklearn.py
    │   │   │   ├── regTrees.py
    │   │   │   ├── sklearn-regressTree-demo.py
    │   │   │   └── treeExplore.py
    │   └── tensorflow2.x
    │   │   ├── Emotion
    │   │       ├── EmotionData.xlsx
    │   │       ├── EmotionData的副本.xlsx
    │   │       ├── Emotion_acc.png
    │   │       ├── Emotion_loss.png
    │   │       ├── neg.xlsx
    │   │       └── pos.xlsx
    │   │   ├── config.py
    │   │   ├── overfit_and_underfit.py
    │   │   ├── poetry.txt
    │   │   ├── quickstart.py
    │   │   ├── test.ipynb
    │   │   ├── text_Emotion.py
    │   │   ├── text_PoetryModel.py
    │   │   ├── text_bert.py
    │   │   ├── text_classification.py
    │   │   ├── text_regression.py
    │   │   └── zh-NER-keras-master
    │   │       ├── .gitignore
    │   │       ├── README.md
    │   │       ├── bilsm_crf_model.py
    │   │       ├── process_data.py
    │   │       ├── train.py
    │   │       └── val.py
    ├── script.py
    └── tool
    │   ├── DecisionTree_getInfoGain.py
    │   └── python2libsvm.py
├── tutorials
    ├── AI常用函数说明.md
    ├── RecommenderSystems
    │   ├── rs_content_demo.py
    │   └── rs_rating_demo.py
    ├── keras
    │   ├── __init__.py
    │   ├── brat_tag.py
    │   └── text_NER.py
    └── test.ipynb
└── update.sh


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1 | # 01\. Python 工具


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1 | # 02\. Python 基础


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1 | # 03\. Numpy


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1 | # 04\. Scipy


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1 | # 05\. Python 进阶


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1 | # 06\. Matplotlib


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1 | # 07\. 使用其他语言进行扩展


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1 | # 08\. 面向对象编程


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1 | # 09\. Theano 基础


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1 | # 10\. 有趣的第三方模块


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1 | # 11\. 有用的工具


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1 | # 12\. Pandas


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1 | # PyTorch 简介


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1 | # PyTorch 神经网络基础


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1 | # 建造第一个神经网络


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1 | # 高级神经网络结构


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1 | # 高阶内容


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1 | # 莫烦 PyTorch 系列教程
2 | 


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/old/ads.txt:
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1 | google.com, pub-3565452474788507, DIRECT, f08c47fec0942fa0


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/old/requirements.txt:
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1 | numpy
2 | pandas
3 | sklearn
4 | keras==2.3.1
5 | tensorflow==2.0.0
6 | git+https://www.github.com/keras-team/keras-contrib.git


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/old/run_example.py:
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 1 | import tutorials.keras.text_NER as ft
 2 | 
 3 | 
 4 | def main():
 5 |     ft.main()
 6 | 
 7 | 
 8 | if __name__ == "__main__":
 9 |     main()
10 | 


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/update.sh:
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1 | git add -A
2 | git commit -am "$(date "+%Y-%m-%d %H:%M:%S")"
3 | git push


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