C++ Data Structures and Algorithms: Build effective, maintainable and readable code in C++ By 作者: Wisnu Anggoro ISBN-10 书号: 1788835212 ISBN-13 书号: 9781788835213 出版日期: 2018-06-11 pages 页数: 409 $44.99 Book Description to Finelybook sorting C++ is a general-purpose programming language which has evolved over the years and is used to develop software for many different sectors. This book will be your companion as it takes you through implementing classic data structures and algorithms to help you get up and running as a confident C++ programmer. We begin with an introduction to C++ data structures and algorithms while also covering essential language constructs. Next, we will see how to store data using linked lists, arrays, stacks, and queues. Then, we will learn how to implement different sorting algorithms, such as quick sort and heap sort. Along with these, we will dive into searching algorithms such as linear search, binary search and more. Our next mission will be to attain high performance by implementing algorithms to string datatypes and implementing hash structures in algorithm design. We’ll also analyze Brute Force algorithms, Greedy algorithms, and more. By the end of the book, you’ll know how to build components that are easy to understand, debug, and use in different applications. Contents 1: LEARNING DATA STRUCTURES AND ALGORITHMS IN C++ 2: STORING DATA IN LISTS AND LINKED LISTS 3: CONSTRUCTING STACKS AND QUEUES 4: ARRANGING DATA ELEMENTS USING A SORTING ALGORITHM 5: FINDING OUT AN ELEMENT USING SEARCHING ALGORITHMS 6: DEALING WITH THE STRING DATA TYPE 7: BUILDING A HIERARCHICAL TREE STRUCTURE 8: ASSOCIATING A VALUE TO A KEY IN A HASH TABLE 9: IMPLEMENTATION OF ALGORITHMS IN REAL LIFE What You Will Learn Know how to use arrays and lists to get better results in complex scenarios Build enhanced applications by using hashtables, dictionaries, and sets Implement searching algorithms such as linear search, binary search, jump search, exponential search, and more Have a positive impact on the efficiency of applications with tree traversal Explore the design used in sorting algorithms like Heap sort, Quick sort, Merge sort and Radix sort Implement various common algorithms in string data types Find out how to design an algorithm for a specific task using the common algorithm paradigms Authors Wisnu Anggoro Wisnu Anggoro is a Microsoft Certified Professional in C# programming and an experienced C/C++ developer. He has also authored the books Boost.Asio C++ Network Programming – Second Edition and Functional C# by Packt. He has been programming since he was in junior high school, which was about 20 years ago, and started developing computer applications using the BASIC programming language in the MS-DOS environment. He has solid experience in smart card programming, as well as desktop and web application programming, including designing, developing, and supporting the use of applications for SIM Card Operating System Porting, personalization, PC/SC communication, and other smart card applications that require the use of C# and C/C++. He is currently a senior smart card software engineer at CIPTA, an Indonesian company that specializes in innovation and technology for smart cards. He can be reached through his email at wisnu@anggoro.net

Data_Structures_and_Algorithms This project write by C++ 暂时没什么要说的

经典的MM优化算法的通俗教程，英文原版，介绍了如何构造Majorization函数以及Minorization函数的常见方法，值得参考。

Data Structures and Algorithms with Python，2015年最新出版

An introduction of computational algebraic geometry

变异量子因式分解 介绍 该存储库包含Eric R. Anschuetz，Jonathan P. Olson，AlánAspuru-Guzik，Yudong Cao的文章“可变量子因式”中提出的算法的实现。 它在上。 代码中的符号直接指的是本文中的符号。 我讲了这个项目，这可能是一个很好的介绍。 您可以找到它并且幻灯片在presentation.pdf文件的此存储库中。 由于QAOA是算法的重要组成部分，因此，如果您不熟悉它，您可能会发现很有帮助。 要求 该项目严重依赖pyquil和grove库。 不幸的是，在我开发该项目时，发行版中存在一些对该项目至关重要的错误。 因此，我从源代码安装了它们： pyquil，提交sha： f22a851d5803e0a6aa73b236c25d28a5fcdb0116 格罗夫，commit-sha： dc6bf6ec63e8c435fe52b1e

Introduction To Algorithms 3rd Edition（算法导论英文版最新），超清，可打印哦

GNN算法 图神经网络相关算法重构及实现教程。 受到pytorch_geometric启发，我们开发了基于Tensorflow的GNN库： ，其中集成了高效且对科研工作者友好的GNN模型。GNN-algorighms则是基于tf_geometric对近几年如火如荼的图神经模型进行此类以及以及手把手教大家实现GNN模型的教程。 目录 本人才疏学浅，如教程有任何不妥当或错误之处，欢迎扫描下方的二维码加群或者开问题讨论。同时本群也欢迎志同道合之士加群共同探讨图神经网络。AI恒久远，GNN永流传。（由于GNN-algorithms交流群人数已经超过200人，只能通过邀请进群，有意者请扫码加我微信，邀你进群）

随机傅立叶特征 该存储库提供Python模块rfflearn ，该模块是用于内核方法的随机傅立叶特征[1，2]的库，如支持向量机和高斯过程模型。 该模块的功能包括： 模块的接口非常接近 ， 支持向量分类器和高斯进程回归器/分类器，提供CPU / GPU训练和推理， 与接口，可更轻松地进行超参数调整， 该存储库提供了，该显示RFF对于实际的机器学习任务很有用。 现在，此模块支持以下方法： 方法 CPU支援 GPU支持 典型相关分析 rfflearn.cpu.RFFCCA -- 高斯过程回归 rfflearn.cpu.RFFGPR rfflearn.gpu.RFFGPR 高斯过程分类 rfflearn.cpu.RFFGPC rfflearn.gpu.RFFGPC 主成分分析 rfflearn.cpu.RFFPCA rfflearn.gpu.RFFPCA 回归 rff

分布估计算法（Estimate Distributation Algorithms：EDAs）优化算法matlab程序