python 音频分析程序，QT界面

说明：  插入cohesive单元, 便于用户在ABAQUS使用时方便插入cohesive单元材料(insert cohesive element)

用于物流选择，可靠性好，结果精确，已经用于实际问题(Used for logistics selection, good reliability, accurate results)

遗传算法源代码,遗传算法源代码，遗传算法源代码( U9057 u4F20 u7B97 u6CD5 u6E90 u4EE3 )

基于python2.7的数字图像识别deeplearning算法

说明：  几种LLE（局部线性嵌入）算法的python实例，有数据集。(Several Python examples of LLE (local linear embedding) algorithms have datasets.)

说明：  《Python学习手册(第3版)》是作者根据过去10年用于教学而广为人知的培训课程的材料编写而成的。除了有许多详实说明和每章小结之外，每章还包括一个头脑风暴：这是《Python学习手册(第3版)》独特的一部分，配合以实用的练习题和复习题，让读者练习新学的技巧并测试自己的理解程度。(The Python Learning Manual (3rd Edition) was compiled by the author on the basis of well-known training materials for teaching in the past 10 years. In addition to many detailed explanations and summaries of each chapter, each chapter also includes a brainstorming: this is a unique part of Python Learning Manual (3rd edition), with practical exercises and review questions, allowing readers to practice new learning skills and test their understanding.)

说明：  本文是2016 台湾资料科学年会前导课程“一天搞懂深度学习”的全部讲义PPT（共268页），由台湾大学电机工程学助理教授李宏毅主讲。作者在文中分四个部分对神经网络的原理、目前存在形态以及未来的发展进行了介绍。深度学习的每一个核心概念在文中都有相关案例进行呈现，通俗易懂。一天的时间搞懂深度学习？其实并不是没有可能。(This is the entire handout PPT (268 pages in total) of "a day to understand deep learning", the leading course of the 2016 Taiwan annual conference of data science. It was given by li hongyi, assistant professor of electrical engineering at Taiwan university.In this paper, the author introduces the principle, existing form and future development of neural network in four parts.Each core concept of deep learning is presented in relevant cases, which are easy to understand.)

Test for google.protobuf.text_format.

说明：  基于Python的神经网络代码，用于识别0-9的手写数字字符(Python based neural network code for recognizing handwritten numeric characters 0-9)

说明：  DenseNet201卷积神经网络训练模型，python语言编程，粗略训练，入门难度。(DenseNet201 convolutional neural network training model, python programming, rough training, entry difficulty.)