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说明：  利用卷积神经网络进行特征提取，并将卷积特征可视化(Feature extraction using convolutional neural networks and visualization of convolution features)

gcn

【实例简介】

python文件，可以对新闻等文本进行分词，然后根据每个词出现的次数进行排序，展示出现次数最多的词语，形成词云。(Python file, can be news and other text segmentation, and then according to the number of times each word to sort, show the most frequently appeared words, the formation of word cloud.)

说明：  完全免费的机器学习实战中文版和英文版资料(Machine learning materials)

通过Python生成一个周期内正弦波数组(sine wave array.Direct digital synthesis, sine wave 0-2pi period, phase to amplitude is one-to-one correspondence.First, the sine wave query table needs to be stored, and then under the clock, through the phase accumulation module and address query module to achieve the sine wave signal.)

吴恩达深度学习第一课第二周编程作业，供大家借鉴共享(DeepLearning Lesson 1, Week 2 Programming Assignments)

abaqus加周期性边界条件，很不错的资料。python脚本文件(the file is used for applying periodic boundary condition on abaqus )

有关于D2D通信中，信道仿真的编程是基于python语言的。(Programming for channel emulation in D2D communication)

第1章　赋予计算机学习数据的能力 1.1　构建智能机器将数据转化为知识 1.2　机器学习的三种不同方法 1.2.1　通过监督学习对未来事件进行预测 1.2.2　通过强化学习解决交互式问题 1.2.3　通过无监督学习发现数据本身潜在的结构 1.2.4　基本术语及符号介绍 1.3　构建机器学习系统的蓝图(Chapter 1 Enables Computers to Learn Data 1.1 Building Intelligent Machines to Transform Data into Knowledge 1.2 Three Different Methods of Machine Learning 1.2.1 Prediction of future events through supervised learning 1.2.2 Solving Interactive Problems through Reinforcement Learning 1.2.3 Discovering the Potential Structure of Data by Unsupervised Learning 1.2.4 Introduction of Basic Terminology and Symbols 1.3 Blueprint for Building Machine Learning System)