《基础几何学》分为八章，讲解了连结、分隔与对称－－定性平面几何；平面性与定量平面几何基础理论；圆与三角学；空间中的平行与垂直；向量几何和向量代数；坐标解析几何简介；球面几何和球面三角学；圆锥截线的故事内容。

本书精心策划了三个虚拟项目，将数据科学家必需的专业技能融合其中，教会读者如何将数据存储到计算机内存中，如何在必要的时候转换内存中的数据值，如何用R编写自己的程序并将其用于数据分析和模拟运行。读者将跟随世界一流的RStudio培训师掌握宝贵的编程技能，并借助这些技能成为优秀的数据科学家。

本书是《SQL基础教程》作者MICK为志在向中级进阶的数据库工程师编写的一本SQL技能提升指南。全书可分为两部分，第一部分介绍了SQL语言不同寻常的使用技巧，带领读者从SQL常见技术，比如CASE表达式、自连接、HAVING子句、外连接、关联子查询、EXISTS……去探索新发现。这部分不仅穿插讲解了这些技巧背后的逻辑和相关知识，而且辅以丰富的示例程序，旨在帮助读者提升编程水平；第二部分着重介绍关系数据库的发展史，把实践与理论结合起来，旨在帮助读者加深对关系数据库和SQL语言的理解。此外，每节末尾均设置有练习题，并在书末提供了解答，方便读者检验自己对书中知识点的掌握程度。

你认为自己了解Java多少?你是个爱琢磨的代码侦探吗?你是否曾经花费数天时间去追踪一个由Java或其类库的陷阱和缺陷而导致的bug?你喜欢智力测验吗?本书正好适合你!
Bloch和Gafter继承了Effective Java一书的传统，深入研究了Java编程语言及其核心类库的细微之处。本书特写了95个噩梦般的谜题，中间穿插着许多有趣的视觉幻象，寓教于乐。任何具备Java知识的人都可以理解这些谜题，但甚至是最老练的程序员也会觉得它们具有挑战性。
多数的谜题都是些小程序，其行为诡秘，不可貌相。你能指出它们会做什么吗?根据这些谜题用到的特性以及各题的详细解惑方案，我们把它们松散地分成了几个部分。这些解惑方案超越了对程序行为的简单解释，向你展示下如何一劳永逸地避免底层的陷阱与缺陷。在本书的后面，有一个方便的陷阱和缺陷目录，可供以后参考。
一旦你解决了这些谜题，那些曾经愚弄过最具经验的Java程序员的隐晦且有违直觉的语言行为，将再也无法把你骗过。

《选举几何学》内容简介：“绝对公平的选举是不可能实现的!”当美国经济学家K.J.Arrow在1952年向世界发表这一定理时，人们才开始真正认识决策和民主。自此，选举学正式成为一种独立完整的理论。《选举几何学》从介绍Arrow定理及其简化版的证明入手，进而讨论后Arrow时代选举理论的面貌，即D.G.Saari（他创建了初等几何学方法）和G.Chichilnisky（她创建了拓扑方法）对选举理论所作的重要贡献。阅读《选举几何学》可以了解社会发展中令人意想不到的真实轨迹，更重要的是，学会如何应用最为恰当的选择方法，让智慧指导生活决策。《选举几何学》可供管理人员、决策人员等社会各界人士阅读，也可供高等院校及科研机构的数理社会学研究人员、相关专业师生参考和使用。

'This book covers the dominant theoretical approaches to the approximate solution of hard combinatorial optimization and enumeration problems. It contains elegant combinatorial theory, useful and interesting algorithms, and deep results about the intrinsic complexity of combinatorial problems. Its clarity of exposition and excellent selection of exercises will make it accessible and appealing to all those with a taste for mathematics and algorithms' - Richard Karp, University Professor, University of California at Berkeley. Following the development of basic combinatorial optimization techniques in the 1960s and 1970s, a main open question was to develop a theory of approximation algorithms. In the 1990s, parallel developments in techniques for designing approximation algorithms as well as methods for proving hardness of approximation results have led to a beautiful theory. The need to solve truly large instances of computationally hard problems, such as those arising from the Internet or the human genome project, has also increased interest in this theory. The field is currently very active, with the toolbox of approximation algorithm design techniques getting always richer. It is a pleasure to recommend Vijay Vazirani's well-written and comprehensive book on this important and timely topic. "I am sure the reader will find it most useful both as an introduction to approximability as well as a reference to the many aspects of approximation algorithms' - Laszlo Lovasz, Senior Researcher, Microsoft Research.

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics.Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

Digital technologies have changed architecture--the way it is taught, practiced, managed, and regulated. But if the digital has created a "paradigm shift" for architecture, which paradigm is shifting? In The Alphabet and the Algorithm, Mario Carpo points to one key practice of modernity: the making of identical copies. Carpo highlights two examples of identicality crucial to the shaping of architectural modernity: in the fifteenth century, Leon Battista Alberti's invention of architectural design, according to which a building is an identical copy of the architect's design; and, in the nineteenth and twentieth centuries, the mass production of identical copies from mechanical master models, matrixes, imprints, or molds. The modern power of the identical, Carpo argues, came to an end with the rise of digital technologies. Everything digital is variable. In architecture, this means the end of notational limitations, of mechanical standardization, and of the Albertian, authorial way of building by design. Charting the rise and fall of the paradigm of identicality, Carpo compares new forms of postindustrial digital craftsmanship to hand-making and the cultures and technologies of variations that existed before the coming of machine-made, identical copies. Carpo reviews the unfolding of digitally based design and construction from the early 1990s to the present, and suggests a new agenda for architecture in an age of variable objects and of generic and participatory authorship.

《工程电路分析》(第7版)首版于1962年，目前已是第七版。得益于作者长期教学经验的积累，《工程电路分析》(第7版)已被国外许多著名大学选为电子、电力工程领域入门课程的教材。作者从3个最基本的科学定律(欧姆定律、基尔霍夫电压定律和基尔霍夫电流定律)推导出了电路分析中常用的分析方法及分析工具。书中首先介绍电路的基本参量以及电路的基本概念，然后结合基尔霍夫电压和电流定律，介绍节点和网孔分析法以及叠加定理、电源变换等常用电路分析方法，并将运算放大器作为电路元件加以介绍；交流电路的分析开始于电容、电感的时域电路特性，然后分析RLC电路的正弦稳态响应，并介绍交流电路的功率分析方法，接着还对多相电路、磁耦合电路的性能分析进行了介绍；为了使读者更深入了解电路的频域特性，《工程电路分析》(第7版)还介绍了复频率、拉普拉斯变换和s域分析、频率响应、傅里叶分析、二端口网络等内容。作者注重将理论和实践相结合，很多例题、练习、章后习题还是正文中的应用实例都取自于业界的典型应用，这也是《工程电路分析》(第7版)的一大特色。

An essential guide to the trouble spots and oddities of R. In spite of the quirks exposed here, R is the best computing environment for most data analysis tasks. R is free, open-source, and has thousands of contributed packages. It is used in such diverse fields as ecology, finance, genomics and music. If you are using spreadsheets to understand data, switch to R. You will have safer -- and ultimately, more convenient -- computations.

《蚁群优化算法》围绕蚁群算法这一来自昆虫世界的优化思想，对其基本原理、核心步骤及其在最优化相关领域的实现作了详细介绍。主要内容包括蚁群算法基本原理、蚁群算法在TSP及其扩展问题求解中的应用、蚁群算法在VRP及其扩展问题求解中的应用、蚁群算法在最优树问题求解中的应用、蚁群算法在整数规划问题求解中的应用、一般连续优化问题的蚁群算法以及多目标蚁群算法等。书中还给出了一些主要算法的Delphi程序实现源代码，可供参考或修改使用。

《非线性最优化基础》从凸分析的观点全面系统地介绍了非线性最优化的基本理论，是国际著名优化专家Masao Fulkushima教授的最新力作。书中不仅详尽透彻地讲解了(光滑与非光滑优化问题、半定规划问题等)各类优化问题的最优性理论、稳定性理论、灵敏度分析、对偶性理论以及相关的凸分析基础等，还深入介绍了变分不等式问题、非线性互补问题以及均衡约束数学规划问题等均衡问题的最新结果。
《非线性最优化基础》既可作为相关专业高年级本科生和研究生的教材，也可作为相关科研人员的参考书。

This well-accepted introduction to computational geometry is a textbook for high-level undergraduate and low-level graduate courses. The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms. In this third edition, besides revisions to the second edition, new sections discussing Voronoi diagrams of line segments, farthest-point Voronoi diagrams, and realistic input models have been added.

本书是一本在大学中广泛使用的经典数学教科书。书中讲解了许多计算机科学中用到的数学知识和技巧，教你如何把一个实际问题一步步演化为数学模型，然后通过计算机解决它，特别着墨于算法分析方面，其主要内容涉及和式、整值函数、数论、二项式系数、特殊的数、生成函数、离散概率、渐近式等，都是编程所必备的知识。
书中不仅讲述了数学问题和技巧，而且教导解决问题的方法，解说深入浅出，妙趣横生。大师们诙谐、细腻的笔触，描绘着数学工作中的欢乐和忧伤，那些或平淡、或深刻、或严肃、或幽默的涂鸦，更让我们在轻松愉悦的心境下体会数学的美妙。
本书面向从事计算机科学、计算数学、计算技术诸方面工作的人员，以及高等院校相关专业的师生。

大数据是当前最为流行的热点概念之一，其已由技术名词衍生到对很多行业产生颠覆性影响的社会现象，作为最明确的技术发展趋势之一，基于大数据的各种新型产品必将会对每个人的日常生活产生日益重要的影响。
《大数据日知录：架构与算法》从架构与算法角度全面梳理了大数据存储与处理的相关技术。大数据技术具有涉及的知识点异常众多且正处于快速演进发展过程中等特点，其技术点包括底层的硬件体系结构、相关的基础理论、大规模数据存储系统、分布式架构设计、各种不同应用场景下的差异化系统设计思路、机器学习与数据挖掘并行算法以及层出不穷的新架构、新系统等。《大数据日知录：架构与算法》对众多纷繁芜杂的相关技术文献和系统进行了择优汰劣并系统性地对相关知识分门别类地进行整理和介绍，将大数据相关技术分为大数据基础理论、大数据系统体系结构、大数据存储，以及包含批处理、流式计算、交互式数据分析、图数据库、并行机器学习的架构与算法以及增量计算等技术分支在内的大数据处理等几个大的方向。通过这种体系化的知识梳理与讲解，相信对于读者整体和系统地了解、吸收和掌握相关的优秀技术有极大的帮助与促进作用。
《大数据日知录：架构与算法》的读者对象包括对NoSQL 系统及大数据处理感兴趣的所有技术人员，以及有志于投身到大数据处理方向从事架构师、算法工程师、数据科学家等相关职业的在校本科生及研究生。

本书出自近世代数领域的两位巨匠之手, 是一本经典的教材。全书共分为15章, 内容包括：整数、有理数和域、多项式、实数、复数、群、向量与向量空间、矩阵代数、线性群、行列式与标准型、布尔代数与格、超限算术、环与理想、代数数域和伽罗瓦理论等。
本书适合数学专业及其他理工科专业高年级本科生和研究生使用, 是一本非常有价值的教材和参考书。

一直以来CPU内部是绝大多数IT工程师难以触及的领域。纵使学习过计算机架构相关课程，自己动手实现CPU也始终遥不可及，因为这涉及计算机系统的最底层——芯片设计。而近年来FPGA芯片产品的发展与普及打破了这一阻碍，利用内部电路可重编程的FPGA，我们几乎可以实现任何逻辑电路，自然也包括CPU。
本书就是在这样一个背景下孕育而生的。本书利用FPGA，为读者开启了一个崭新的自制CPU的世界。全书分为3章，分别介绍计算机系统最底层的3个部分：CPU设计制作、电路板设计制造以及汇编编程。将如此广泛的技术内容以实践的方式融合成一册，该书可谓首屈一指。
本书可以帮助软件工程师深入了解硬件与底层，开发出高效代码。硬件工程师可以在本书基础上设计定制硬件，开发高速计算机系统。相信所有读者都可以在本书的阅读过程中，体会到自制计算机系统的乐趣与热情。

His ideas have had a profound influence on twentieth-century work on logic and the foundations of mathematics.

"Introduction to Computing Systems: From bits & gates to C & beyond", now in its second edition, is designed to give students a better understanding of computing early in their college careers in order to give them a stronger foundation for later courses. The book is in two parts: the underlying structure of a computer, and programming in a high level language and programming methodology. To understand the computer, the authors introduce the LC-3 and provide the LC-3 Simulator to give students hands-on access for testing what they learn. To develop their understanding of programming and programming methodology, they use the C programming language.The book takes a "motivated" bottom-up approach, where the students first get exposed to the big picture and then start at the bottom and build their knowledge bottom-up. Within each smaller unit, the same motivated bottom-up approach is followed. Every step of the way, students learn new things, building on what they already know. The authors feel that this approach encourages deeper understanding and downplays the need for memorizing. Students develop a greater breadth of understanding, since they see how the various parts of the computer fit together.

《计算机病毒防范艺术》作者是赛门铁克（Symantec）公司安全响应中心首席安全架构师，他根据自己设计和改进Norton AntiVirus系统产品及培训病毒分析人员的过程中遇到的问题精心总结编写了本书。本书最大的特色是大胆深入地探讨了病毒知识的技术细节，从病毒的感染策略上深入分析病毒的复杂性，从文件、内存和网络等多个角度讨论病毒的感染技术，对过去20年来黑客们开发的各种病毒技巧进行了分类和讲解，并介绍了代码变形和其他新兴病毒感染技术，展示了当前计算机病毒和防毒软件最新技术，向读者传授计算机病毒分析和防护的方法学。