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A new version of the classic and widely used text adapted for the JavaScript programming language. Since the publication of its first edition in 1984 and its second edition in 1996, Structure and Interpretation of Computer Programs (SICP) has influenced computer science curricula around the world. Widely adopted as a textbook, the book has its origins in a popular entry-level computer science course taught by Harold Abelson and Gerald Jay Sussman at MIT. SICP introduces the reader to central ideas of computation by establishing a series of mental models for computation. Earlier editions used the programming language Scheme in their program examples. This new version of the second edition has...
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was de...
Note: Teaches simplified characters, used in mainland China--not so useful in Taiwan.
Strategies for building large systems that can be easily adapted for new situations with only minor programming modifications. Time pressures encourage programmers to write code that works well for a narrow purpose, with no room to grow. But the best systems are evolvable; they can be adapted for new situations by adding code, rather than changing the existing code. The authors describe techniques they have found effective--over their combined 100-plus years of programming experience--that will help programmers avoid programming themselves into corners. The authors explore ways to enhance flexibility by: Organizing systems using combinators to compose mix-and-match parts, ranging from small functions to whole arithmetics, with standardized interfaces Augmenting data with independent annotation layers, such as units of measurement or provenance Combining independent pieces of partial information using unification or propagation Separating control structure from problem domain with domain models, rule systems and pattern matching, propagation, and dependency-directed backtracking Extending the programming language, using dynamically extensible evaluators
An extensively revised edition of a mathematically rigorous yet accessible introduction to algorithms.
The new edition of a classic text that concentrates on developing general methods for studying the behavior of classical systems, with extensive use of computation. We now know that there is much more to classical mechanics than previously suspected. Derivations of the equations of motion, the focus of traditional presentations of mechanics, are just the beginning. This innovative textbook, now in its second edition, concentrates on developing general methods for studying the behavior of classical systems, whether or not they have a symbolic solution. It focuses on the phenomenon of motion and makes extensive use of computer simulation in its explorations of the topic. It weaves recent disco...
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.
In Computing for Ordinary Mortals, cognitive scientist and AI expert Robert St. Amant explains what he calls, "the really interesting part" of computing, which are the ideas behind the technology. They're powerful ideas, and the foundations for everything that computers do, but they are little discussed. This book will not tell you how to use your computer, but it will give you a conceptual tour of how it works. Some of the ideas, like modularity which are so embedded in what we do as humans, can also give us insight into our own daily activities, how we interact with other people, and in some cases even what's going on in our heads. Computing is all around us, and, to quote Richard Hamming, the influential mathematician and computer scientist, "The purpose of computing is insight, not numbers," and it is this insight that informs the entire book.
Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.
Essays by leading theoretical linguists—including Noam Chomsky, B. Elan Dresher, Richard Kayne, Howard Lasnik, Morris Halle, Norbert Hornstein, Henk van Riemsdijk, and Edwin Williams—reflect on Jean-Roger Vergnaud's influence in the field and discuss current theoretical issues Jean-Roger Vergnaud's work on the foundational issues in linguistics has proved influential over the past three decades. At MIT in 1974, Vergnaud (now holder of the Andrew W. Mellon Professorship in Humanities at the University of Southern California) made a proposal in his Ph.D. thesis that has since become, in somewhat modified form, the standard analysis for the derivation of relative clauses. Vergnaud later int...