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此 CHM 文档的内容均为 CSDN 众网友共同收集而来，由网友们于 2004 年 3 月 7 日在 www.csdn.net 网站 VC/MFC 版的非技术类论坛上正式提出整理工作的倡议，经王国凡同志（sgnaw 李逍遥）整理而成，以供大家工作学习参考之用。 我自认为是一个比较热心的人，经常帮助同学同事们解决 IT 方面的问题，有时也逛逛 CSDN。我在武汉出身，也在武汉工作三年了，希望将来能为 IT 业的发展作出贡献。整理工作虽然辛苦，但也快乐，错漏之处再所难免，如有建议或意见请联系 sgnaw@163.com(CHM contents of this document are the common netizen CSDN collected from the public, from users in March 7, 2004 in www.csdn.net site VC/MFC version of the non-technical categories of the official presentation of the Forum on the initiative of finishing the work by Where the Kingdom of Comrade (sgnaw Li Xiaoyao) collated from for everyone to learn the work of reference. Since I think is a more enthusiastic, often to help students solve IT colleagues issues, and sometimes go CSDN. I am born in Wuhan, Wuhan is also working for three years and hopefully in the future for the IT industry to contribute to the development. While finishing work hard, but also happy, errors and omissions are inevitable and then, if the recommendations or comments please contact sgnaw@163.com)

华为OJ训练平台的基础篇的所有题目答案，已总结为各种类型，写成子函数，可以直接调用(Huawei OJ Basics training platform for all the questions answers are summarized for all types, written subroutines can be called directly)

说明：  这是一部学习c++必看的经典教程 c++primer 中文第三版(This is a learning c++ Classic must-see tutorial c++ Primer Chinese third edition)

说明：  个人代码库，VC6+ACCESS。增删改查，最小化托盘等。(Personal code library, VC6+ ACCESS. Additions and deletions to the investigation, the smallest of the tray.)

Nehe的opengl全部教程，适用于c++语言，适合初学者。(All Nehe' s opengl tutorials for c++ language, suitable for beginners.)

经典的C语言问题。495个各种C问题与解决办法。可以很好的帮助你掌握c语言(The classic C language problems. 495 various C problems and solutions. Could very well help you to master the c language)

c++完美版本，纯中文，深入分析C++的对象等难点重点。(c perfect version of pure Chinese, in-depth analysis of the C key targets such difficult.)

这是一本详细讲解C语言数值计算方法的书，几乎涉及岛数值计算的所有内容。(This is an elaborate in detail the numerical method for C language book, Numerical Calculation of the island almost all of its contents.)

基于高斯过程的机器学习，其中包括回归问题和分类问题(machine learning)