很好在编程语言 Python 实现电脑游戏"井字游戏"

说明：  dc motor contro using python and c__

python绘制一个图形示例源码(tkinter)

说明：  训练小型CNN网络，处理MNIST数据机(small-scale CNN network training, in order to process MNIST dataset)

python设计模式第2版 学习python Python3程序开发指南(python design mode, for python learn.)

采用svm算法对酒进行分类，效果还行，准确率97%左右，python语言(Using SVM algorithm to classify wine, the effect is good, the accuracy is about 97%. Python language)

随机生成一个大的数，并保证其是素数

《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.)

说明：  python源码剖析，带详细目录，觉得好请点赞(Python source code analysis)

说明：  在具有至少十五个节点的网络中模拟洪泛路由。每个数据包应包含一个计数器（n = 10），该计数器在每一跳上递减。(Simulate flood routing in a network with at least fifteen nodes. Each packet should contain a counter (n=10) that is decremented on each hop. When the counter gets to zero, the packet is discarded. Time is discrete, and each link can handle only one packet per time interval (i.e. only one packet in total may traverse the link in either direction). Nodes should include a buffer to queue any additional packets. Present your results in terms of the number of duplicate packets produced, and the congestion at each node, and suggest a possible solution for reducing this problem.)

Mises模型UMAT代码，可用于ABAqus二次开发。