用python编的打外星人游戏

复合材料冲击损伤ew2e23e232e22ge(Impact Damage of Composite Materials)

说明：  使用python实现计算器，基本实现计算器所需要的全部功能，非常适合用来测试(operator, Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy)

说明：  利用python的深度学习优化算法，比如优化算法：Adam,RmsProp等(DeepLearning optimize algorithm by python such as optimize algorithm Adam,rmsprop and so on)

nao机器人的平衡程序，这是nao机器人比赛用的程序，可以人机互动和演示。(Nao robot balancing process, which is the NAO robot contest with the program, you can interact and demonstration.)

《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.)

用树莓派实现人脸识别，通过分析出的表情播放音乐(Using raspberry pie to realize face recognition and play music)

Python OBDII库；

爬虫，简单语句，爬虫快速 支持单线程操作，容易改正，并有注释(Reptiles, simple statement, reptiles fast support single-threaded operation, easy to correct, and Notes)

说明：  附有论文，交通信号灯识别源程序。采DDPG深度强化学习方法。给出了LOSS损失函数图像(With the paper, traffic signal recognition source program.)

说明：  python gui开发基础，一些简单的pythonGUI代码(the base of python GUI)