<b>A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.</b><br /><br />The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem.<br /><br />The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.

Git is the version control system developed by Linus Torvalds for Linux kernel development. It took the open source world by storm since its inception in 2005, and is used by small development shops and giants like Google, Red Hat, and IBM, and of course many open source projects.
* A book by Git experts to turn you into a Git expert
* Introduces the world of distributed version control
* Shows how to build a Git development workflow
What you’ll learn
* Use Git as a programmer or a project leader.
* Become a fluent Git user.
* Use distributed features of Git to the full.
* Acquire the ability to insert Git in the development workflow.
* Migrate programming projects from other SCMs to Git.
* Learn how to extend Git.
This book is for all open source developers: you are bound to encounter it somewhere in the course of your working life. Proprietary software developers will appreciate Git’s enormous scalability, since it is used for the Linux project, which comprises thousands of developers and testers.

You've experienced the shiny, point-and-click surface of your Linux computer-now dive below and explore its depths with the power of the command line. The Linux Command Line takes you from your very first terminal keystrokes to writing full programs in Bash, the most popular Linux shell. Along the way you'll learn the timeless skills handed down by generations of gray-bearded, mouse-shunning gurus: file navigation, environment configuration, command chaining, pattern matching with regular expressions, and more. In addition to that practical knowledge, author William Shotts reveals the philosophy behind these tools and the rich heritage that your desktop Linux machine has inherited from Unix supercomputers of yore. As you make your way through the book's short, easily-digestible chapters, you'll learn how to: * Create and delete files, directories, and symlinks * Administer your system, including networking, package installation, and process management * Use standard input and output, redirection, and pipelines * Edit files with Vi, the world's most popular text editor * Write shell scripts to automate common or boring tasks * Slice and dice text files with cut, paste, grep, patch, and sed Once you overcome your initial "shell shock," you'll find that the command line is a natural and expressive way to communicate with your computer. Just don't be surprised if your mouse starts to gather dust.

Rigorously updated, with a new modular format, the second edition of Learning and Memory brings a modern perspective to the study of this key topic. Reflecting the growing importance of neuroscience in the field, it compares brain studies and behavioural approaches in human and other animal species, and is available in full-color throughout.

This book focuses on a conceptual flaw in contemporary artificial intelligence and cognitive science. Many people have discovered diverse manifestations and facets of this flaw, but the central conceptual impasse is at best only partially perceived. Its consequences, nevertheless, visit themselves as distortions and failures of multiple research projects - and make impossible the ultimate aspirations of the fields. The impasse concerns a presupposition concerning the nature of representation - that all representation has the nature of encodings: encodingism. Encodings certainly exist, but encodingism is at root logically incoherent; any programmatic research predicted on it is doomed too distortion and ultimate failure. The impasse and its consequences - and steps away from that impasse - are explored in a large number of projects and approaches. These include SOAR, CYC, PDP, situated cognition, subsumption architecture robotics, and the frame problems - a general survey of the current research in AI and Cognitive Science emerges. Interactivism, an alternative model of representation, is proposed and examined.

Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence.
Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence.
The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.

Sams Teach Yourself SAP in 24 Hours, Second Edition is the perfect tool for learning one of the most sophisticated enterprise solutions available today. Designed to being with the basics, you will become acquainted with the entire SAP system, from navigation to creating your own reports. You'll also cover:

Implementation tools and methodologies
NetWeaver
ECC 5.0
Designing Screens and menus
Reporting
Integration with Microsoft Office
And more Written by leading SAP consultants with over 20 years of combined experience, this easy-to-understand tutorial is ideal for getting up and running with SAP quickly and efficiently. </P>

On its publication in 1957, The Poverty of Historicism was hailed by Arthur Koestler as 'probably the only book published this year which will outlive the century.'
A devastating criticism of fixed and predictable laws in history, Popper dedicated the book to all those 'who fell victim to the fascist and communist belief in Inexorable Laws of Historical Destiny.' Short and beautifully written, it has inspired generations of readers, intellectuals and policy makers. One of the most important books on the social sciences since the Second World War, it is a searing insight into the ideas of this great thinker.

这本书收集了约60道算法和程序设计题目，这些题目大部分在近年的笔试、面试中出现过，或者是被微软员工热烈讨论过。作者试图从书中各种有趣的问题出发，引导读者发现问题，分析问题，解决问题，寻找更优的解法。本书的内容分为下面几个部分：
（1）游戏之乐：从游戏和其他有趣问题出发，化繁为简，分析总结。
（2）数字之魅：编程的过程实际上就是和数字及字符打交道的过程。这一部分收集了一些好玩的对数字进行处理的题目。
（3）结构之法：汇集了常见的对字符串、链表、队列，以及树等进行操作的题目。
（4）数学之趣：列举了一些不需要写具体程序的数学问题，锻炼读者的抽象思维能力。
书中绝大部分题目都提供了详细的解说。 每道题目后面还有一至两道扩展问题，供读者进一步钻研。
书中还讲述了面试的各种小故事，告诉读者微软需要什么样的技术人才，重视什么样的能力，如何甄别人才。回答读者关于IT业面试，招聘，职业发展的疑问。这本书的很多题目会出现在IT 行业的各种笔试、面试中，但这本书更深层的意义在于引导读者思考，和读者共享思考之乐，编程之美。

这本书主要介绍系统软件的运行机制和原理，涉及在Windows和Linux两个系统平台上，一个应用程序在编译、链接和运行时刻所发生的各种事项，包括：代码指令是如何保存的，库文件如何与应用程序代码静态链接，应用程序如何被装载到内存中并开始运行，动态链接如何实现，C/C++运行库的工作原理，以及操作系统提供的系统服务是如何被调用的。每个技术专题都配备了大量图、表和代码实例，力求将复杂的机制以简洁的形式表达出来。本书最后还提供了一个小巧且跨平台的C/C++运行库MiniCRT，综合展示了与运行库相关的各种技术。
对装载、链接和库进行了深入浅出的剖析，并且辅以大量的例子和图表，可以作为计算机软件专业和其他相关专业大学本科高年级学生深入学习系统软件的参考书。同时，还可作为各行业从事软件开发的工程师、研究人员以及其他对系统软件实现机制和技术感兴趣者的自学教材。

JAVA PROGRAMMING, Sixth Edition provides the beginning programmer with a guide to developing applications using the Java programming language. Java is popular among professional programmers because it can be used to build visually interesting GUI and Web-based applications. Java also provides an excellent environment for the beginning programmer - students can quickly build useful programs while learning the basics of structured and object-oriented programming techniques.

is a printed version of Bruce Eckel's online materials that provides a useful perspective on mastering Java for those with previous programming experience. The author's take on the essence of Java as a new programming language and the thorough introduction to Java's features make this a worthwhile tutorial.

This market leading text on computational theory provides a mathematical treatment of computer science theory designed around theorems and proofs.

A Treatise of Human Nature (1739-40), David Hume's comprehensive attempt to base philosophy on a new, observationally grounded study of human nature, is one of the most important texts in Western philosophy. It is also the focal point of current attempts to understand 18th-century philosophy. The Treatise first explains how we form such concepts as cause and effect, external existence, and personal identity, and to form compelling but unconfirmable beliefs in the entities represented by these concepts. It then offers a novel account of the passions, explains freedom and necessity as they apply to human choices and actions, and concludes with detailed explanations of how we distinguish between virtue and vice and of the different kinds of virtue. Hume's Abstract of the Treatise, also included in the volume, outlines his 'chief argument' regarding our conception of, and belief in, cause and effect. The texts printed in this volume are those of the critical edition of Hume's philosophical works now being published by the Clarendon Press. The volume includes a substantial introduction explaining the aims of the Treatise as a whole and of each of its ten parts, extensive annotations, a glossary of terms, a comprehensive index, and suggestions for further reading.

Andrew Hodges's biography of Alan Turing, the brilliant Cambridge mathematician who masterminded the cracking of the German Enigma code and indeed was the the father of the modern computer, was regarded as 'the paperback buy of the season' (Sunday Times) when it was first published. It is now reissued in Vintage with a new preface.

This volume is a theoretical and practical approach to the design of computer technology.

Structure and Interpretation of Computer Programs has had a dramatic impact on computer science curricula over the past decade. This long-awaited revision contains changes throughout the text.
There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published.
A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises.
In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.