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已选条件
  1. 编程语言:Python
  2. 代码类别:Windows
  3. 发布时间:不限
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1. knn

说明:  以图像处理和knn算法为基础,利用knn算法,在python开发环境中设计了一个手写数字识别系统,该系统采用28*28的模板对图新分成784块提取手写数字的784个特征,在二值图像数据基础上,通过朴素贝叶斯分类器算法,对0~9这十类手写数字进行学习和分类。(Based on image processing and KNN algorithm, a handwritten digit recognition system is designed in Python development environment by using KNN algorithm. The system uses 28*28 template to divide the graph into 784 blocks to extract 784 features of handwritten digits. On the basis of binary image data, it learns and classifies the ten types of handwritten digits, 0-9, through Naive Bayesian classifier algorithm.)

4
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89
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2019-04-29发布

2. convlstm

  实现卷积lstm的代码,也是从网上找的,大家可以参考(The code to implement convolutional LSTM is also found on the internet. You can refer to it.)

4
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98
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2019-04-17发布

3. convlstm

说明:  实现卷积lstm的代码,也是从网上找的,大家可以参考(The code to implement convolutional LSTM is also found on the internet. You can refer to it.)

7
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116
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2019-04-17发布

4. vgg16

  用tensorflow实现vgg深度学习网络(Realization of VGg deep learning network with tensorflow)

4
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67
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2019-04-03发布

5. vgg16

说明:  用tensorflow实现vgg深度学习网络(Realization of VGg deep learning network with tensorflow)

6
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64
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2019-04-03发布

6. example1

  运用格子搜索法确定SVR中的参数c和gamma(Using Lattice Search Method to Determine Parameters C and Gamma in SVR)

1
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53
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2019-03-06发布

7. example1

说明:  运用格子搜索法确定SVR中的参数c和gamma(Using Lattice Search Method to Determine Parameters C and Gamma in SVR)

4
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88
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2019-03-06发布

8. test

  elastic search 的python测试运行(Python test run of elastic search)

0
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68
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2019-02-16发布

9. test

说明:  elastic search 的python测试运行(Python test run of elastic search)

0
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66
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2019-02-16发布

10. Recommender-Systems-master

  使用协同过滤的推荐系统测试代码Predicting movie ratings using collaborative filtering and latent concept extractors based on matrix decomposition methods like SVD and CUR on the movielens-100k dataset The project explores techniques for predicting unknown user ratings based on a large dataset of users and movie ratings.(Recommender-SystemsWe used 6 different recommender methods to predict user ratings across the data sets. Namely we set up Collaborative Filtering along with its baseline variant and Matrix decomposition techniques like Singular Value Decomposition and CUR. Moreover, we also implemented dimensionality reduction in these matrix decomposition techniques which preserved 90% of the energy so as to increase the computational efficiency while keeping the accuracy similar for these methods.)

2
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84
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2019-01-13发布

11. Recommender-Systems-master

说明:  使用协同过滤的推荐系统测试代码Predicting movie ratings using collaborative filtering and latent concept extractors based on matrix decomposition methods like SVD and CUR on the movielens-100k dataset The project explores techniques for predicting unknown user ratings based on a large dataset of users and movie ratings.(Recommender-SystemsWe used 6 different recommender methods to predict user ratings across the data sets. Namely we set up Collaborative Filtering along with its baseline variant and Matrix decomposition techniques like Singular Value Decomposition and CUR. Moreover, we also implemented dimensionality reduction in these matrix decomposition techniques which preserved 90% of the energy so as to increase the computational efficiency while keeping the accuracy similar for these methods.)

3
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53
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2019-01-13发布

12. IM

  在线即使通信 登陆模块 添加好友模块 私聊模块 群聊模块(On-line even communication Landing module Add Friends Module Private chat module Group chat module)

0
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81
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2019-01-08发布

13. IM

说明:  在线即使通信 登陆模块 添加好友模块 私聊模块 群聊模块(On-line even communication Landing module Add Friends Module Private chat module Group chat module)

0
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61
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2019-01-08发布

14. pyz1

  在基于python3.6 的pycharm 平台上,使用pyqt5搭建的窗口程序参考代码。(Based on python3.6,in develop plat pycharm2008,we use pyqt5 build a windows app.)

5
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127
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2018-12-08发布

15. house_predict

  房价预测系统,利用python语句实现,在读入数据后,利用神经网络训练数据特征,从而实现推荐。(The house price forecasting system is realized by Python statement. After reading the data, the data features are trained by neural network to realize recommendation.)

7
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75
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2018-12-03发布

16. Gotsu

  用遗传算法和otsu实现多彩色图像的多阈值分割 。。。。。。。。。。。。(Multi threshold segmentation based on genetic algorithm)

8
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76
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2018-10-03发布

17. 处理大全升级版

  进行电离层电子密度反演是与标准数据的对比分析(The inversion of ionospheric electron density is a comparison with standard data)

4
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69
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2018-09-15发布

18. numpy pandas

  python numpy 的一些基本操作和结果展示。。。。。。。(python numpy basic function)

2
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94
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2018-05-16发布

19. 191769c0dbfbad4b

  工厂模式 这是一个的代码 ,利用起来非常牛逼,得到写的(Factory model ,Figure 2 shows the approach, and you might recognize the abstract factory pattern)

0
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101
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2018-05-14发布

20. Python逆向最大匹配实现-代码-文档-截图等

  对于文本进行自然语言处理,中文分词。北邮计算机院NLP课的作业。(This is a homework for BUPT student, implementing the word segment of natural language processing.)

16
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66
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2018-05-13发布