Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.
The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.
By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.

This short introduction to category theory is for readers with relatively little mathematical background. At its heart is the concept of a universal property, important throughout mathematics. After a chapter introducing the basic definitions, separate chapters present three ways of expressing universal properties: via adjoint functors, representable functors, and limits. A final chapter ties the three together.
For each new categorical concept, a generous supply of examples is provided, taken from different parts of mathematics. At points where the leap in abstraction is particularly great (such as the Yoneda lemma), the reader will find careful and extensive explanations.

Category theory is unmatched in its ability to organize and layer abstractions and to find commonalities between structures of all sorts. No longer the exclusive preserve of pure mathematicians, it is now proving itself to be a powerful tool in science, informatics, and industry. By facilitating communication between communities and building rigorous bridges between disparate worlds, applied category theory has the potential to be a major organizing force. This book offers a self-contained tour of applied category theory. Each chapter follows a single thread motivated by a real-world application and discussed with category-theoretic tools. We see data migration as an adjoint functor, electrical circuits in terms of monoidal categories and operads, and collaborative design via enriched profunctors. All the relevant category theory, from simple to sophisticated, is introduced in an accessible way with many examples and exercises, making this an ideal guide even for those without experience of university-level mathematics.

本书使用向量的概念对国内高校工科“线性代数”的课程内容进行了较全面的几何分析。从向量的几何意义开始，分别讲述了向量组、向量空间、行列式、矩阵、线性方程组和二次型的几何意义或几何解释，其中不乏重要概念的物理意义的解释。这本书就像一串项梁，把上百个概念和定理的几何意义串在一起敬献给读者朋友。
本书文字多为作者原创，比如叉积的物理意义，克莱姆法则、雅可比矩阵、相似/合同矩阵、转置矩阵/对偶、矩阵乘积的行列式等系列概念的几何意义等，应用方面如使用矩阵分析的方法分析电子振荡器的工作原理等。
本书图文并茂，思路清晰、语言流畅，概念及定理解释得合理、自然，同时具有通俗性、科普性，由于本书是直接根据线性代数课程的要求进行解释的，除了适合初学者和自学者使用之外，特别适合正在学习或复习线性代数的大学生作为深入思考的辅导书籍使用。

20世纪最后一位数学史大师，
克莱因被最多读者阅读的一本书。
……
音乐能激起或平静人的心灵，绘画能愉悦人的视觉，
诗歌能激发人的感情，哲学能使思想得到满足，
工程技术能改善人的物质生活，
数学则能够做到所有这一切。
……
25个世纪以来，数学史上发生了三次危机：非欧几何对欧氏 几何的冲击、无理数的发现及数的扩张 、微积分带来的分析困境；集合论悖论和其他逻辑悖论出现……使得数学大厦一次次面临倒塌的危险……
本书探讨数千年来数学在直觉、逻辑、应用之间穿梭往复的炫目旅程，再现真实数学的发展过程，阐述数学的起源、数学的繁荣和科学的数学化，直到当代数学的现状：数学与确定性（逻辑，严密性，完备性）渐行渐远。
克莱因透过数学史上的大事件一步一步剥开数学思想与数学思维变迁的脉络。
……
数学不是天然的宝石，只是人工的。
在今天，绝大多数聪明人依然相信物理世界的真理与人类理性的严密，本书正是要打破这一迷信。
……
数学家靠的不是运算准确、迅速，而是数学思维——数学是一种思考方式。
克莱因能够几乎不借助公式，用数学来解析思想，将数千年的 数学探讨如此深入，非常之了得。

由于计算机的迅猛发展，与其关系密切的递推式数学考题常出现在每年的高考中，而中学数学中恰无此内容，这就造成严重脱节现象。本书就是针对此客观存在的不合理脱节，为全国高中师生补充这部分“营养”
本书内容有从递推式求数列通项、部分和、极限，从通项求递推式等。书中备有大量例题和习题，大多出自全国高考题和美、日竞赛题。书末附有习题答案，供读者参考。
本书是中学师生的教学参考书，也可供有兴趣读者参考使用。

Now available in paperback, this successful radical approach to complex analysis replaces the standard calculational arguments with new geometric ones. With several hundred diagrams, and far fewer prerequisites than usual, this is the first visual intuitive introduction to complex analysis. Although designed for use by undergraduates in mathematics and science, the novelty of the approach will also interest professional mathematicians.

本書有五大內容重點：
一．用最簡單的範例全面引介Wavelet的發展動機、基礎理論及計算方法。
二．複習並補充數學知識
三．略J研究Wavelet理論，並瞭解它的應用原理和演算及法規。
四．利用Wavelet轉換作訊號處理的程式與範例。
五．利用Wavelet作數值計算的程式與範例。
本書適合已學過微積分和線性代數者以及大學三年級電子、電機系的學生使用。

Aimed at undergraduate mathematics and computer science students, this book is an excellent introduction to a lot of problems of discrete mathematics. It discusses a number of selected results and methods, mostly from areas of combinatorics and graph theory, and it uses proofs and problem solving to help students understand the solutions to problems. Numerous examples, figures, and exercises are spread throughout the book.

This book is a clear and self-contained introduction to discrete mathematics. Aimed mainly at undergraduate and early graduate students of mathematics and computer science, it is written with the goal of stimulating interest in mathematics and an active, problem-solving approach to the presented material. The reader is led to an understanding of the basic principles and methods of actually doing mathematics (and having fun at that). Being more narrowly focused than many discrete mathematics textbooks and treating selected topics in an unusual depth and from several points of view, the book reflects the conviction of the authors, active and internationally renowned mathematicians, that the most important gain from studying mathematics is the cultivation of clear and logical thinking and habits useful for attacking new problems. More than 400 enclosed exercises with a wide range of difficulty, many of them accompanied by hints for solution, support this approach to teaching. The readers will appreciate the lively and informal style of the text accompanied by more than 200 drawings and diagrams.Specialists in various parts of science with a basic mathematical education wishing to apply discrete mathematics in their field can use the book as a useful source, and even experts in combinatorics may occasionally learn from pointers to research literature or from presentations of recent results. Invitation to Discrete Mathematics should make a delightful reading both for beginners and for mathematical professionals. The main topics include: elementary counting problems, asymptotic estimates, partially ordered sets, basic graph theory and graph algorithms, finite projective planes, elementary probability and the probabilistic method, generating functions, Ramsey's theorem, and combinatorial applications of linear algebra. General mathematical notions going beyond the high-school level are thoroughly explained in the introductory chapter. An appendix summarizes the undergraduate algebra needed in some of the more advanced sections of the book.

In this substantive yet accessible book, pioneering software designer Alexander Stepanov and his colleague Daniel Rose illuminate the principles of generic programming and the mathematical concept of abstraction on which it is based, helping you write code that is both simpler and more powerful.
If you’re a reasonably proficient programmer who can think logically, you have all the background you’ll need. Stepanov and Rose introduce the relevant abstract algebra and number theory with exceptional clarity. They carefully explain the problems mathematicians first needed to solve, and then show how these mathematical solutions translate to generic programming and the creation of more effective and elegant code. To demonstrate the crucial role these mathematical principles play in many modern applications, the authors show how to use these results and generalized algorithms to implement a real-world public-key cryptosystem.
As you read this book, you’ll master the thought processes necessary for effective programming and learn how to generalize narrowly conceived algorithms to widen their usefulness without losing efficiency. You’ll also gain deep insight into the value of mathematics to programming–insight that will prove invaluable no matter what programming languages and paradigms you use.
You will learn about
How to generalize a four thousand-year-old algorithm, demonstrating indispensable lessons about clarity and efficiency
Ancient paradoxes, beautiful theorems, and the productive tension between continuous and discrete
A simple algorithm for finding greatest common divisor (GCD) and modern abstractions that build on it
Powerful mathematical approaches to abstraction
How abstract algebra provides the idea at the heart of generic programming
Axioms, proofs, theories, and models: using mathematical techniques to organize knowledge about your algorithms and data structures
Surprising subtleties of simple programming tasks and what you can learn from them
How practical implementations can exploit theoretical knowledge

Chris Evans将参演马克·韦布（超凡蜘蛛侠系列）执导新片《Gifted》。该片讲述美队扮演一名原本波士顿大学助教现在是修船工的Frank Adler在姐姐自杀后领养了外甥女Mary——一位智力过人的天才少女。Mary刚一入学就表现得与众不同，然而舅舅Frank只想让孩子过普通人生活。Mary的外婆得知了少女的天赋，出现在二人的生活里，要将Mary培养成数学天才。于是一场抚养权之争开始了。