gatbx

说明：  Delphi下用Intraweb开发WEB程序应用实战(Developing WEB Application with Intraweb under Delphi)

说明：  一款C语言代码方法搜索手册，方便写代码的字典(A C language code method search manual, easy to write code dictionary)

我找到的一些有关于图像分割的论文,可以作为了解图像分割的材料.(I found some papers on image segmentation, image segmentation can be used as understanding the material.)

说明：  Qt5.10 GUI完全参考手册，基础入门，本书适合希望使用Qt C++开发跨平台应用程序的读者阅读。(Qt5.10 GUI complete reference manual, basic introduction, this book is suitable for readers who want to use QT C + + to develop cross platform applications.)

说明：  procedure of matlab which is used to cultivated

说明：  C++11的官方文档，英文版，用于学习C++11.(C++ 11 official document, English version, for learning C++ 11.)

Indy In Depth。indy网络开发技术的深度指南，适合入门、提高各阶段。(Indy In Depth. indy web development technologies depth guide is suitable for entry and improve the various stages.)

matlab program编程英文影印版(photocopy of the English version of programmed matlab program)

说明：  C++语言程序设计基础，清华大学郑莉教授电子讲义。(C++ Language Programming Foundation, Electronic Lecture by Professor Zheng Li of Tsinghua University.)

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.)