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GTD (Getting Things Done) 一書的workbook(GTD (Getting Things Done) book 1 workbook)

说明：  无线网状网基于不确定性度量极小化的信任模型(In wireless mesh networks,the sample space of evidence may be not integrative.)

说明：  经典的C++编程资料，有助于建立面对对象的编程习惯(Classical C++ Programming book)

matlab+vc混合编程相关书籍，需要的请下载(matlab+vc,if you want it,please download!)

详细介绍了第一章 Visual FoxPro基础 第二章 VF 的系统初步 第三章 数据与数据运算 第四章 VF数据库及其操作 (The first chapter introduces the basic Visual FoxPro Chapter II Chapter III VF system preliminary data and data operations database and its operations Chapter VF)

编程珠玑是一门比较核心的技术，上传只供想学习的人(biancheng zhu ji Core Programming is a relatively core)

嵌入式系统设计师软考复习资料，网上收集到的，上传分享给大家(The embedded system designer software review)

经典C语言书上的练习的答案，手边放一本非常方便。C语言的学习光看书没有用，必须做练习，这个答案帮助很大。(The C Answer Book. Solutions to the Exercises in The C Programming Language, Second Edition by Brian W. Kernighan and Dennis M. Ritchie)

如何在首页显示当前的让你的主页能够自动识别来访者使用的浏览器； 一种一条一条显示信息的跑马灯； 自动滚屏并不一定需要Dhtml，到这里看看喔！ 在页面上提供向前，向后翻页的按钮。 告诉来访者在本页面停留的时间，作用好坏你判断吧！ 请来客登记姓名，统计来访次数。等等 ，还有很多很多原码等着你来看哦~(Home show the current home page you can automatically identify visitors to use the browser; One shows a message of a 5,250; Auto Scroll Dhtml not necessarily need to see here! The pages provide forward and backward scrolling button. Tell visitors stay in the pages of time, the role of good or bad judgment you! Invited guests registered to the name, the number of visitors statistics. And so on and many source waiting for you to look at oh)

说明：  《Python数据挖掘入门与实践》高清中文版 本书作为数据挖掘入门读物，介绍了数据挖掘的基础知识、基本工具和实践方法，通过循序渐进地讲解算法，带你轻松踏上数据挖掘之旅。本书采用理论与实践相结合的方式，呈现了如何使用决策树和随机森林算法预测美国职业篮球联赛比赛结果，如何使用亲和性分析方法推荐电影，如何使用朴素贝叶斯算法进行社会媒体挖掘，等等。本书也涉及神经网络、深度学习、大数据处理等内容。本书面向愿意学习和尝试数据挖掘的程序员。("Python Data Mining Getting Started and Practice" HD Chinese version As a primer on data mining, this book introduces the basic knowledge, basic tools and practical methods of data mining. By step-by-step explanation of the algorithm, you can easily embark on the journey of data mining. This book uses a combination of theory and practice, showing how to use the decision tree and random forest algorithm to predict the results of the American professional basketball league game, how to use the affinity analysis method to recommend movies, how to use the naive Bayesian algorithm for social media mining ,and many more. This book also covers neural networks, deep learning, big data processing and more. This book is for programmers who are willing to learn and experiment with data mining.)