# Tensorflow **Repository Path**: wangp06/Tensorflow ## Basic Information - **Project Name**: Tensorflow - **Description**: Tensorflow实战学习笔记、代码、机器学习进阶系列 - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 2 - **Created**: 2024-04-09 - **Last Updated**: 2024-04-09 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README ## Tensorflow- - [Tensorflow实战学习笔记](./tensorflow_in_action) - [机器学习进阶系列](./MachinLN) - [tensorflow实战代码](./Tensorflow) - [人脸检测系列](./face_detection) - [tensorflow api解读](./tf-API) - [机器学习实战代码注释](./ml_in_action) - [tensorflow2_tutorials_chinese](https://github.com/czy36mengfei/tensorflow2_tutorials_chinese) 欢迎关注微信公众号：MachineLN 对dl感兴趣，还可以关注我的博客，这是我的博客目录：（地址： http://blog.csdn.net/u014365862/article/details/78422372 ） 本文为博主原创文章，未经博主允许不得转载。有问题可以加微信：lp9628(注明CSDN)。 公众号MachineLN，邀请您扫码关注： ![image](http://upload-images.jianshu.io/upload_images/4618424-3ef1722341ba72d2?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240) **机器学习进阶系列：(下面内容在微信公众号同步)** 1. [机器学习-1：MachineLN之三要素](http://blog.csdn.net/u014365862/article/details/78955063) 2. [机器学习-2：MachineLN之模型评估](http://blog.csdn.net/u014365862/article/details/78959353) 3. [机器学习-3：MachineLN之dl](http://blog.csdn.net/u014365862/article/details/78980142) 4. [机器学习-4：DeepLN之CNN解析](http://blog.csdn.net/u014365862/article/details/78986089) 5. [机器学习-5：DeepLN之CNN权重更新（笔记）](http://blog.csdn.net/u014365862/article/details/78959211) 6. [机器学习-6：DeepLN之CNN源码](http://blog.csdn.net/u014365862/article/details/79010248) 7. [机器学习-7：MachineLN之激活函数](http://blog.csdn.net/u014365862/article/details/79007801) 8. [机器学习-8：DeepLN之BN](http://blog.csdn.net/u014365862/article/details/79019518) 9. [机器学习-9：MachineLN之数据归一化](http://blog.csdn.net/u014365862/article/details/79031089) 10. [机器学习-10：MachineLN之样本不均衡](http://blog.csdn.net/u014365862/article/details/79040390) 11. [机器学习-11：MachineLN之过拟合](http://blog.csdn.net/u014365862/article/details/79057073) 12. [机器学习-12：MachineLN之优化算法](http://blog.csdn.net/u014365862/article/details/79070721) 13. [机器学习-13：MachineLN之kNN](http://blog.csdn.net/u014365862/article/details/79091913) 14. [机器学习-14：MachineLN之kNN源码](http://blog.csdn.net/u014365862/article/details/79101209) 15. [](http://mp.blog.csdn.net/postedit/79135612)[机器学习-15：MachineLN之感知机](http://blog.csdn.net/u014365862/article/details/79135612) 16. [机器学习-16：MachineLN之感知机源码](http://blog.csdn.net/u014365862/article/details/79135767) 17. [机器学习-17：MachineLN之逻辑回归](http://blog.csdn.net/u014365862/article/details/79157777) 18. [机器学习-18：MachineLN之逻辑回归源码](http://blog.csdn.net/u014365862/article/details/79157841) 19. [机器学习-19：MachineLN之SVM（1）](http://blog.csdn.net/u014365862/article/details/79184858) 20. [机器学习-20：MachineLN之SVM（2）](http://blog.csdn.net/u014365862/article/details/79202089) 21. [机器学习-21：MachineLN之SVM源码](http://blog.csdn.net/u014365862/article/details/79224119) 22. [机器学习-22：MachineLN之RL](http://blog.csdn.net/u014365862/article/details/79240997) **人脸检测系列：** 1. [人脸检测——AFLW准备人脸](http://blog.csdn.net/u014365862/article/details/74682464) 2. [人脸检测——生成矫正人脸——cascade cnn的思想， 但是mtcnn的效果貌似更赞](http://blog.csdn.net/u014365862/article/details/74690865) 3. [人脸检测——准备非人脸](http://blog.csdn.net/u014365862/article/details/74719498) 4. [人脸检测——矫正人脸生成标签](http://blog.csdn.net/u014365862/article/details/74853099) 5. [人脸检测——mtcnn思想，生成negative、positive、part样本。](http://blog.csdn.net/u014365862/article/details/78051411) 6. [**人脸检测——滑动窗口篇（训练和实现）**](http://blog.csdn.net/u014365862/article/details/77816493) 7. [**人脸检测——fcn**](http://blog.csdn.net/u014365862/article/details/78036382) 8. [简单的人脸跟踪](http://blog.csdn.net/u014365862/article/details/77989896) 9. [Face Detection(OpenCV) Using Hadoop Streaming API](http://blog.csdn.net/u014365862/article/details/78173740) 10. [Face Recognition(face_recognition) Using Hadoop Streaming API](http://blog.csdn.net/u014365862/article/details/78175803) 11. [非极大值抑制（Non-Maximum-Suppression）](http://blog.csdn.net/u014365862/article/details/53376516) **OCR系列：** **1. [tf20: CNN—识别字符验证码](http://blog.csdn.net/u014365862/article/details/53869816)** 2. [**身份证识别——生成身份证号和汉字**](http://blog.csdn.net/u014365862/article/details/78581949) 3. [**tf21: 身份证识别——识别身份证号**](http://blog.csdn.net/u014365862/article/details/78582128) 4. **[tf22: ocr识别——不定长数字串识别](http://blog.csdn.net/u014365862/article/details/78582417)** **机器学习，深度学习系列:** 1. [反向传播与它的直观理解](http://blog.csdn.net/u014365862/article/details/54728707) 2. [卷积神经网络（CNN）：从原理到实现](http://blog.csdn.net/u014365862/article/details/54865609) 3. [机器学习算法应用中常用技巧-1](http://blog.csdn.net/u014365862/article/details/54890040) 4. [机器学习算法应用中常用技巧-2](http://blog.csdn.net/u014365862/article/details/54890046) 5. [一个隐马尔科夫模型的应用实例：中文分词](http://blog.csdn.net/u014365862/article/details/54891582) 6. [**Pandas处理csv表格**](http://blog.csdn.net/u014365862/article/details/54923429) 7. [sklearn查看数据分布](http://blog.csdn.net/u014365862/article/details/54973495) 8. [TensorFlow 聊天机器人](http://blog.csdn.net/u014365862/article/details/57518873) 9. [YOLO](http://blog.csdn.net/u014365862/article/details/60321879) 10. [感知机--模型与策略](http://blog.csdn.net/u014365862/article/details/61413859) 11. [从 0 到 1 走进 Kaggle](http://blog.csdn.net/u014365862/article/details/72794198) 12. [python调用Face++，玩坏了！](http://blog.csdn.net/u014365862/article/details/74149097) 13. [人脸识别keras实现教程](http://blog.csdn.net/u014365862/article/details/74332028) 14. [机器学习中的Bias(偏差)，Error(误差)，和Variance(方差)有什么区别和联系？](http://blog.csdn.net/u014365862/article/details/76360351) 15. [CNN—pooling层的作用](http://blog.csdn.net/u014365862/article/details/77159143) 16. [trick—Batch Normalization](http://blog.csdn.net/u014365862/article/details/77159778) 17. [**tensorflow使用BN—Batch Normalization**](http://blog.csdn.net/u014365862/article/details/77188011) 18. [trick—Data Augmentation](http://blog.csdn.net/u014365862/article/details/77193754) 19. [CNN图图图](http://blog.csdn.net/u014365862/article/details/77367172) 20. [为什么很多做人脸的Paper会最后加入一个Local Connected Conv？](http://blog.csdn.net/u014365862/article/details/77795902) 21. [**Faster RCNN：RPN，anchor，sliding windows**](http://blog.csdn.net/u014365862/article/details/77887230) 22. [**深度学习这些坑你都遇到过吗？**](http://blog.csdn.net/u014365862/article/details/77961624) 23. [**image——Data Augmentation的代码**](http://blog.csdn.net/u014365862/article/details/78086604) 24. [8种常见机器学习算法比较](http://blog.csdn.net/u014365862/article/details/52937983) 25. [几种常见的激活函数](http://blog.csdn.net/u014365862/article/details/52710698) 26. [**Building powerful image classification models using very little data**](http://blog.csdn.net/u014365862/article/details/78519629) 27. [**机器学习模型训练时候tricks**](http://blog.csdn.net/u014365862/article/details/78519727) 28. [OCR综述](https://handong1587.github.io/deep_learning/2015/10/09/ocr.html#handwritten-recognition) 29. [一个有趣的周报](http://blog.csdn.net/u014365862/article/details/78757109) 30. [根据已给字符数据，训练逻辑回归、随机森林、SVM，生成ROC和箱线图](http://blog.csdn.net/u014365862/article/details/78835541) **图像处理系列：** 1. [python下使用cv2.drawContours填充轮廓颜色](http://blog.csdn.net/u014365862/article/details/77720368) 2. [imge stitching图像拼接stitching](http://blog.csdn.net/u014365862/article/details/53433048) 3. [用python简单处理图片（1）：打开\显示\保存图像](http://blog.csdn.net/u014365862/article/details/52652256) 4. [用python简单处理图片（2）：图像通道\几何变换\裁剪](http://blog.csdn.net/u014365862/article/details/52652273) 5. [用python简单处理图片（3）：添加水印](http://blog.csdn.net/u014365862/article/details/52652296) 6. [用python简单处理图片（4）：图像中的像素访问](http://blog.csdn.net/u014365862/article/details/52652300) 7. [用python简单处理图片（5）：图像直方图](http://blog.csdn.net/u014365862/article/details/52652309) 8. [**仿射变换，透视变换：二维坐标到二维坐标之间的线性变换，可用于landmark人脸矫正。**](http://blog.csdn.net/u014365862/article/details/78678872) **代码整合系列：** 1. [windows下C++如何调用matlab程序](http://blog.csdn.net/u014365862/article/details/77480325) 2. [ubuntu下C++如何调用matlab程序](http://blog.csdn.net/u014365862/article/details/77529096) 3. [matlab使用TCP/IP Server Sockets](http://blog.csdn.net/u014365862/article/details/77745476) 4. [ubuntu下C++如何调用python程序，gdb调试C++代码](http://blog.csdn.net/u014365862/article/details/77864743) 5. [How to pass an array from C++ to an embedded python](http://blog.csdn.net/u014365862/article/details/77891487) 6. [如何使用Python为Hadoop编写一个简单的MapReduce程序](http://blog.csdn.net/u014365862/article/details/78169554) 7. [图像的遍历](http://blog.csdn.net/u014365862/article/details/53513710) 8. [**ubuntu下CMake编译生成动态库和静态库，以OpenTLD为例。**](http://blog.csdn.net/u014365862/article/details/78663269) 9. [**ubuntu下make编译生成动态库，然后python调用cpp。**](http://blog.csdn.net/u014365862/article/details/78675033) **数据结构和算法系列：** 1. [堆排序](http://blog.csdn.net/u014365862/article/details/78200711) 2. [red and black (深度优先搜索算法dfs)](http://blog.csdn.net/u014365862/article/details/48781603) 3. [深度优先搜索算法](http://blog.csdn.net/u014365862/article/details/48729681) 4. [qsort原理和实现](http://blog.csdn.net/u014365862/article/details/48688457) 5. [stack实现queue ; list实现stack](http://blog.csdn.net/u014365862/article/details/48594323) 6. [另一种斐波那契数列](http://blog.csdn.net/u014365862/article/details/48573545) 7. [堆和栈的区别(个人感觉挺不错的)](http://blog.csdn.net/u014365862/article/details/49159499) 8. [排序方法比较](http://blog.csdn.net/u014365862/article/details/52502824) 9. [漫画 ：什么是红黑树？](https://mp.weixin.qq.com/s/JJVbi7kqDpLUuh696J7oLg) 10. [牛客网刷题](https://www.nowcoder.com/activity/oj) 11. [莫烦python 666](https://morvanzhou.github.io/) **kinect 系列：** 1. [Kinect v2.0原理介绍之一：硬件结构](http://blog.csdn.net/u014365862/article/details/46713807) 2. [Kinect v2.0原理介绍之二：6种数据源](http://blog.csdn.net/u014365862/article/details/46849253) 3. [Kinect v2.0原理介绍之三：骨骼跟踪的原理](http://blog.csdn.net/u014365862/article/details/46849309) 4. [Kinect v2.0原理介绍之四：人脸跟踪探讨](http://blog.csdn.net/u014365862/article/details/46849357) 5. [Kinect v2.0原理介绍之五：只检测离kinect最近的人脸](http://blog.csdn.net/u014365862/article/details/47809401) 6. [Kinect v2.0原理介绍之六：Kinect深度图与彩色图的坐标校准](http://blog.csdn.net/u014365862/article/details/48212085) 7. [Kinect v2.0原理介绍之七：彩色帧获取](http://blog.csdn.net/u014365862/article/details/48212377) 8. [Kinect v2.0原理介绍之八：高清面部帧(1) FACS 介绍](http://blog.csdn.net/u014365862/article/details/48212631) 9. [Kinect v2.0原理介绍之九：高清面部帧(2) 面部特征对齐](http://blog.csdn.net/u014365862/article/details/48212757) 10. [Kinect v2.0原理介绍之十：获取高清面部帧的AU单元特征保存到文件](http://blog.csdn.net/u014365862/article/details/48780361) 11. [kinect v2.0原理介绍之十一：录制视频](http://blog.csdn.net/u014365862/article/details/77929405) 12. [Kinect v2.0原理介绍之十二：音频获取](http://blog.csdn.net/u014365862/article/details/49204931) 13. [Kinect v2.0原理介绍之十三：面部帧获取](http://blog.csdn.net/u014365862/article/details/50434088) 14. [Kinect for Windows V2和V1对比开发___彩色数据获取并用OpenCV2.4.10显示](http://blog.csdn.net/u014365862/article/details/48948861) 15. [Kinect for Windows V2和V1对比开发___骨骼数据获取并用OpenCV2.4.10显示](http://blog.csdn.net/u014365862/article/details/48949055) 16. [用kinect录视频库](http://blog.csdn.net/u014365862/article/details/48946543) **tensorflow系列：** 1. [](http://blog.csdn.net/u014365862/article/details/78422315)[Ubuntu 16.04 安装 Tensorflow(GPU支持)](http://blog.csdn.net/u014365862/article/details/53868411) 2. [使用Python实现神经网络](http://blog.csdn.net/u014365862/article/details/53868414) 3. [tf1: nn实现评论分类](http://blog.csdn.net/u014365862/article/details/53868418) 4. [tf2: nn和cnn实现评论分类](http://blog.csdn.net/u014365862/article/details/53868422) 5. [tf3: RNN—mnist识别](http://blog.csdn.net/u014365862/article/details/53868425) 6. [tf4: CNN—mnist识别](http://blog.csdn.net/u014365862/article/details/53868430) 7\.  [tf5: Deep Q Network—AI游戏](http://blog.csdn.net/u014365862/article/details/53868436) 8. [tf6: autoencoder—WiFi指纹的室内定位](http://blog.csdn.net/u014365862/article/details/53868533) 9. [tf7: RNN—古诗词](http://blog.csdn.net/u014365862/article/details/53868544) 10. [tf8:RNN—生成音乐](http://blog.csdn.net/u014365862/article/details/53868549) 11. [tf9: PixelCNN](http://blog.csdn.net/u014365862/article/details/53868557) 12. [tf10: 谷歌Deep Dream](http://blog.csdn.net/u014365862/article/details/53868560) 13. [tf11: retrain谷歌Inception模型](http://blog.csdn.net/u014365862/article/details/53868568) 14. [tf12: 判断男声女声](http://blog.csdn.net/u014365862/article/details/54600398) 15. [tf13: 简单聊天机器人](http://blog.csdn.net/u014365862/article/details/53869660) 16. [tf14: 黑白图像上色](http://blog.csdn.net/u014365862/article/details/53869682) 17. [tf15: 中文语音识别](http://blog.csdn.net/u014365862/article/details/53869701) 18. [tf16: 脸部特征识别性别和年龄](http://blog.csdn.net/u014365862/article/details/53869712) 19. [tf17: “声音大挪移”](http://blog.csdn.net/u014365862/article/details/53869724) 20. [tf18: 根据姓名判断性别](http://blog.csdn.net/u014365862/article/details/53869732) 21\.  [tf19: 预测铁路客运量](http://blog.csdn.net/u014365862/article/details/53869802) 22. [**tf20: CNN—识别字符验证码**](http://blog.csdn.net/u014365862/article/details/53869816) 23. [tf21: 身份证识别——识别身份证号](http://blog.csdn.net/u014365862/article/details/78582128) 24. [](http://blog.csdn.net/u014365862/article/details/78582417)[tf22: ocr识别——不定长数字串识别](http://blog.csdn.net/u014365862/article/details/78582417) 25. [tf23: “恶作剧” --人脸检测](http://blog.csdn.net/u014365862/article/details/53978811) 26. [tf24: GANs—生成明星脸](http://blog.csdn.net/u014365862/article/details/54380277) 27. [](http://blog.csdn.net/u014365862/article/details/54706771)[tf25: 使用深度学习做阅读理解+完形填空](http://blog.csdn.net/u014365862/article/details/54428325) 28. [tf26: AI操盘手](http://blog.csdn.net/u014365862/article/details/54706771) 29. [tensorflow_cookbook--preface](http://blog.csdn.net/u014365862/article/details/70837573) 30. [01 TensorFlow入门（1）](http://blog.csdn.net/u014365862/article/details/70837638) 31. [01 TensorFlow入门（2）](http://blog.csdn.net/u014365862/article/details/70849334) 32. [02 The TensorFlow Way（1）](http://blog.csdn.net/u014365862/article/details/70884624) 33. [02 The TensorFlow Way（2）](http://blog.csdn.net/u014365862/article/details/70887213) 34. [02 The TensorFlow Way（3）](http://blog.csdn.net/u014365862/article/details/71038528) 35. [03 Linear Regression](http://blog.csdn.net/u014365862/article/details/71064855) 36. [04 Support Vector Machines](http://blog.csdn.net/u014365862/article/details/71078010) 37. [tf API 研读1：tf.nn，tf.layers， tf.contrib概述](http://blog.csdn.net/u014365862/article/details/77833481) 38. [tf API 研读2：math](http://blog.csdn.net/u014365862/article/details/77847410) 39. [tensorflow中的上采样(unpool)和反卷积(conv2d_transpose)](http://blog.csdn.net/u014365862/article/details/77936259) 40. [tf API 研读3：Building Graphs](http://blog.csdn.net/u014365862/article/details/77944301) 41. [tf API 研读4：Inputs and Readers](http://blog.csdn.net/u014365862/article/details/77946268) 42. [](http://blog.csdn.net/u014365862/article/details/77967231)[tf API 研读5：Data IO](http://blog.csdn.net/u014365862/article/details/77967231) 43. [tf API 研读6：Running Graphs](http://blog.csdn.net/u014365862/article/details/77967995) 44. [**tf.contrib.rnn.static_rnn与tf.nn.dynamic_rnn区别**](http://blog.csdn.net/u014365862/article/details/78238807) 45. [**Tensorflow使用的预训练的resnet_v2_50，resnet_v2_101，resnet_v2_152等模型预测，训练**](http://blog.csdn.net/u014365862/article/details/78272811) 46. [**tensorflow下设置使用某一块GPU、多GPU、CPU的情况**](http://blog.csdn.net/u014365862/article/details/78292475) 47. [**工业器件检测和识别**](http://blog.csdn.net/u014365862/article/details/78359194) 48. [**将tf训练的权重保存为CKPT,PB ,CKPT 转换成 PB格式。并将权重固化到图里面,并使用该模型进行预测**](http://blog.csdn.net/u014365862/article/details/78404980) 49. **[tensorsor快速获取所有变量，和快速计算L2范数](http://blog.csdn.net/u014365862/article/details/78422315)** 50. [**cnn+rnn+attention**](http://blog.csdn.net/u014365862/article/details/78495870) 51. [Tensorflow实战学习笔记](https://github.com/MachineLP/Tensorflow-) 52. [tf27: Deep Dream—应用到视频](http://blog.csdn.net/u014365862/article/details/53869830) 53. [tf28: 手写汉字识别](http://blog.csdn.net/u014365862/article/details/53869837) 54. [tf29: 使用tensorboard可视化inception_v4](http://blog.csdn.net/u014365862/article/details/79115556) 55. [tf30: center loss及其mnist上的应用](http://blog.csdn.net/u014365862/article/details/79184966) 56. [tf31: keras的LSTM腾讯人数在线预测](http://blog.csdn.net/u014365862/article/details/79186993) 57. [tf32: 一个简单的cnn模型：人脸特征点训练](http://blog.csdn.net/u014365862/article/details/79187157) 58. [tf33: 图片降噪：卷积自编码](http://blog.csdn.net/u014365862/article/details/79246179) **C++系列：** 1. [c++ primer之const限定符](http://blog.csdn.net/u014365862/article/details/46848613) 2. [c++primer之auto类型说明符](http://blog.csdn.net/u014365862/article/details/46849697) 3. [c++primer之预处理器](http://blog.csdn.net/u014365862/article/details/46853869) 4. [c++primer之string](http://blog.csdn.net/u014365862/article/details/46860037) 5. [c++primer之vector](http://blog.csdn.net/u014365862/article/details/46885087) 6. [c++primer之多维数组](http://blog.csdn.net/u014365862/article/details/46933199) 7. [c++primer之范围for循环](http://blog.csdn.net/u014365862/article/details/47706255) 8. [c++primer之运算符优先级表](http://blog.csdn.net/u014365862/article/details/47706423) 9. [c++primer之try语句块和异常处理](http://blog.csdn.net/u014365862/article/details/47707669) 10. [c++primer之函数(函数基础和参数传递)](http://blog.csdn.net/u014365862/article/details/47783193) 11. [c++primer之函数(返回类型和return语句)](http://blog.csdn.net/u014365862/article/details/47808711) 12. [c++primer之函数重载](http://blog.csdn.net/u014365862/article/details/47834667) 13. [c++重写卷积网络的前向计算过程，完美复现theano的测试结果](http://blog.csdn.net/u014365862/article/details/48010697) 14. [c++ primer之类](http://blog.csdn.net/u014365862/article/details/48165685) 15. [c++primer之类（构造函数再探）](http://blog.csdn.net/u014365862/article/details/48198595) 16. [c++primer之类（类的静态成员）](http://blog.csdn.net/u014365862/article/details/48199161) 17. [c++primer之顺序容器（容器库概览）](http://blog.csdn.net/u014365862/article/details/48209805) 18. [c++primer之顺序容器（添加元素）](http://blog.csdn.net/u014365862/article/details/48226673) 19. [c++primer之顺序容器（访问元素）](http://blog.csdn.net/u014365862/article/details/48230053) **OpenCV系列：** 1. [自己训练SVM分类器，进行HOG行人检测。](http://blog.csdn.net/u014365862/article/details/53243604) 2. [opencv-haar-classifier-training](http://blog.csdn.net/u014365862/article/details/53096367) 3. [vehicleDectection with Haar Cascades](http://blog.csdn.net/u014365862/article/details/53087675) 4. [LaneDetection](http://blog.csdn.net/u014365862/article/details/53083143) 5. [OpenCV学习笔记大集锦](http://blog.csdn.net/u014365862/article/details/53063627) 6. [Why always OpenCV Error: Assertion failed (elements_read == 1) in unknown function ?](http://blog.csdn.net/u014365862/article/details/53000619) 7. [目标检测之训练opencv自带的分类器（opencv_haartraining 或 opencv_traincascade）](http://blog.csdn.net/u014365862/article/details/52997019) 8. [车牌识别 之 字符分割](http://blog.csdn.net/u014365862/article/details/52672747) 9. **[仿射变换，透视变换：二维坐标到二维坐标之间的线性变换，可用于landmark人脸矫正。](http://blog.csdn.net/u014365862/article/details/78678872)** 10. [opencv实现抠图（单一背景），替换背景图](http://blog.csdn.net/u014365862/article/details/78863756) **python系列（**web开发、多线程等**）：** 1. [**flask的web开发，用于机器学习（主要还是DL）模型的简单演示。**](http://blog.csdn.net/u014365862/article/details/78818334) 2. **[python多线程，获取多线程的返回值](http://blog.csdn.net/u014365862/article/details/78835348)** 3. [文件中字的统计及创建字典](http://blog.csdn.net/u014365862/article/details/78914151) **其他:** 1. [MAC平台下Xcode配置使用OpenCV的具体方法 (2016最新)](http://blog.csdn.net/u014365862/article/details/53067565) 2. [**python下如何安装.whl包？**](http://blog.csdn.net/u014365862/article/details/51817390) 3. [给中国学生的第三封信：成功、自信、快乐](http://blog.csdn.net/u014365862/article/details/47972321) 4. [自己-社会-机器学习](http://blog.csdn.net/u014365862/article/details/48604145) 5. [不执著才叫看破，不完美才叫人生。](http://blog.csdn.net/u014365862/article/details/49079047) 6. [PCANet的C++代码——详细注释版](http://blog.csdn.net/u014365862/article/details/51213280) 7. [责任与担当](http://blog.csdn.net/u014365862/article/details/51841590) 8. [好走的都是下坡路](http://blog.csdn.net/u014365862/article/details/53244402) 9. [一些零碎的语言，却触动到内心深处。](http://blog.csdn.net/u014365862/article/details/53186012) 10. [用一个脚本学习 python](http://blog.csdn.net/u014365862/article/details/54428373) 11. [一个有趣的周报](http://blog.csdn.net/u014365862/article/details/78757109)