▍1. python语言，一个遗传算法，解决TSP问题
python语言，一个遗传算法，解决TSP问题(python language, a genetic algorithm to solve TSP problems)
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▍2. 手写数字识别
说明： 基于BP神经网络的手写数字识别系统，程序使用python语言编写，训练数据集为mnist；交互界面使用PYQT编写，用户可在画板通过鼠标书写数字作为识别对象。(The program of handwritten digit recognition system based on BP neural network is written in Python language, and the training data set is MNIST; the interactive interface is written in pyqt, and the user can write the digit on the drawing board through the mouse as the recognition object.)
▍3. VRPTW的蚁群算法 ant-for-VRPTW-master
VRPTW的蚁群算法，采用python写法，根据算例并求出最优化路径(Ant colony algorithm based on VRPTW)
▍4. Python深度学习 pdf+代码
本书由Keras之父、现任Google人工智能研究员的弗朗索瓦?肖莱（Franc?ois Chollet）执笔，详尽介绍了用Python和Keras进行深度学习的探索实践，包括计算机视觉、自然语言处理、产生式模型等应用。书中包含30多个代码示例，步骤讲解详细透彻。由于本书立足于人工智能的可达性和大众化，读者无须具备机器学习相关背景知识即可展开阅读。在学习完本书后，读者将具备搭建自己的深度学习环境、建立图像识别模型、生成图像和文字等能力。(This book is written by Franc_ois Chollet, the father of Keras and a current researcher on artificial intelligence at Google. It introduces in detail the exploratory practice of using Python and Keras for in-depth learning, including computer vision, natural language processing, production models and other applications. The book contains more than 30 code examples, the steps to explain in detail. Because the book is based on the accessibility and popularity of artificial intelligence, readers need not have the background knowledge of machine learning to start reading. After learning this book, readers will have the ability to build their own in-depth learning environment, establish image recognition model, generate images and text.)
▍5. stock-rnn-master
说明： 用深度学习算法进行股票价格预测，文件中含有数据集(Using deep learning algorithm to forecast stock price, the file contains data set)
▍6. iris
数据挖掘入门， 鸢尾属植物 iris示例代码(Iris sample code for data mining)
▍7. iris
说明： 数据挖掘入门， 鸢尾属植物 iris示例代码(Iris sample code for data mining)
▍8. scanner
这是一个低级的端口扫描器，用起来不是那么好，但能很快的显示开放的端口。只是线程处理方面有些问题。(This is a low-level port scanner, not so good to use, but can quickly display open ports. There are just some problems with thread processing.)
▍9. scanner
说明： 这是一个低级的端口扫描器，用起来不是那么好，但能很快的显示开放的端口。只是线程处理方面有些问题。(This is a low-level port scanner, not so good to use, but can quickly display open ports. There are just some problems with thread processing.)
▍10. 《图解深度学习》+山下隆义+张弥+密码：GCEDM359
《图解深度学习》是从深度学习的发展历程讲起的，从理论和实践两个方面介绍了深度学习的各种方法，以及深度学习在图像识别等领域的应用案例。内容图文并茂，涉及神经网络、卷积神经网络、受限玻尔兹曼机、自编码器、泛化能力的提高， 并介绍了包括Theano、Pylearn2、Caffe、DIGITS、Chainer 和TensorFlow等深度学习工具的安装和使用方法。书如其名，《图解深度学习》图例非常丰富，清晰直观，适合所有对深度学习感兴趣的读者阅读("Graphic in-depth learning" starts from the development process of in-depth learning. It introduces various methods of in-depth learning from both theoretical and practical aspects, as well as application cases of in-depth learning in image recognition and other fields. The contents are full of pictures and texts, including the improvement of neural network, convolution neural network, restricted Boltzmann machine, self-encoder and generalization ability. The installation and use methods of deep learning tools including Theano, Pylearn2, Caffe, DIGITS, Chainer and TensorFlow are also introduced. As its name implies, the legend of "Graphic in-depth learning" is very rich, clear and intuitive, suitable for all readers interested in in in-depth learning to read.)
▍11. sub
Kaggle competition final submission score 0.985(Kaggle competition final submission score 0.985 fsaaddaewfew5sadf4asf)
▍12. sub
说明： Kaggle competition final submission score 0.985(Kaggle competition final submission score 0.985 fsaaddaewfew5sadf4asf)
▍13. 语言模型
knn手写数字识别，tensorflow教程(Knn Handwritten Number Recognition)
▍14. 语言模型
说明： knn手写数字识别，tensorflow教程(Knn Handwritten Number Recognition)
▍15. VPN批量检测
批量扫描Vps网站的存活性，服务器IP+端口(Survivability of batch scanning Vps websites)
▍16. VPN批量检测
说明： 批量扫描Vps网站的存活性，服务器IP+端口(Survivability of batch scanning Vps websites)
▍17. server 1.4
开启本地HTTP服务，并可以自定义端口，任意文件下载(Open the local HTTP service, and you can customize the port and download any file.)
▍18. server 1.4
说明： 开启本地HTTP服务，并可以自定义端口，任意文件下载(Open the local HTTP service, and you can customize the port and download any file.)
▍19. Python
用Python实现了网页数据的抓取，网页动态图的浮现，字体颜色大小的改变，网页数据爬取，制作相关网页，用表格体现，并改变了表格的风格，(Python is used to capture web page data, the emergence of dynamic graph, the change of font size, the crawl of web page data, the production of relevant web pages, which are represented by tables, and the style of tables is changed.)
▍20. Python
说明： 用Python实现了网页数据的抓取，网页动态图的浮现，字体颜色大小的改变，网页数据爬取，制作相关网页，用表格体现，并改变了表格的风格，(Python is used to capture web page data, the emergence of dynamic graph, the change of font size, the crawl of web page data, the production of relevant web pages, which are represented by tables, and the style of tables is changed.)
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