{pdf download} What Can Be Computed?: A Practical Guide to the Theory of Computation

What Can Be Computed?: A Practical Guide to the Theory of Computation. John MacCormick

What-Can-Be-Computed-A.pdf
ISBN: 9781400889846 | 408 pages | 11 Mb

• What Can Be Computed?: A Practical Guide to the Theory of Computation
• John MacCormick
• Page: 408
• Format: pdf, ePub, fb2, mobi
• ISBN: 9781400889846
• Publisher: Princeton University Press

Download What Can Be Computed?: A Practical Guide to the Theory of Computation

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What Can Be Computed?: A Practical Guide to the Theory of Computation by John MacCormick An accessible and rigorous textbook for introducing undergraduates to computer science theory What Can Be Computed? is a uniquely accessible yet rigorous introduction to the most profound ideas at the heart of computer science. Crafted specifically for undergraduates who are studying the subject for the first time, and requiring minimal prerequisites, the book focuses on the essential fundamentals of computer science theory and features a practical approach that uses real computer programs (Python and Java) and encourages active experimentation. It is also ideal for self-study and reference. The book covers the standard topics in the theory of computation, including Turing machines and finite automata, universal computation, nondeterminism, Turing and Karp reductions, undecidability, time-complexity classes such as P and NP, and NP-completeness, including the Cook-Levin Theorem. But the book also provides a broader view of computer science and its historical development, with discussions of Turing's original 1936 computing machines, the connections between undecidability and Gödel's incompleteness theorem, and Karp's famous set of twenty-one NP-complete problems. Throughout, the book recasts traditional computer science concepts by considering how computer programs are used to solve real problems. Standard theorems are stated and proven with full mathematical rigor, but motivation and understanding are enhanced by considering concrete implementations. The book's examples and other content allow readers to view demonstrations of--and to experiment with—a wide selection of the topics it covers. The result is an ideal text for an introduction to the theory of computation. An accessible and rigorous introduction to the essential fundamentals of computer science theory, written specifically for undergraduates taking introduction to the theory of computation Features a practical, interactive approach using real computer programs (Python in the text, with Java alternatives online) to enhance motivation and understanding Gives equal emphasis to computability and complexity Includes special topics that demonstrate the profound nature of key ideas in the theory of computation Features a companion website that includes additional materials

Computer programming - Wikipedia
The purpose of programming is to find a sequence of instructions that will automate performing a specific task or solving a given problem. The process of programming thus often requires expertise in many different subjects, including knowledge of the application domain, specialized algorithms, and formal logic. Related  The Church-Turing Thesis (Stanford Encyclopedia of Philosophy)
The Church-Turing thesis concerns the concept of an effective or systematic or mechanical method in logic, mathematics and computer science. M will, if carried out without error, produce the desired result in a finite number of steps;; Mcan (in practice or in principle) be carried out by a human being  Browse Princeton Catalog in COMPUTERS - Computer Science
Introduction to Computational Science: Modeling and Simulation for the Sciences - Second Edition: Shiflet, A. and Shiflet, G. (Hardcover and eBook) What CanBe Computed?: A Practical Guide to the Theory of Computation: MacCormick, J. ( Hardcover and eBook)  Theory of computation - Wikipedia
In theoretical computer science and mathematics, the theory of computation is the branch that deals with how efficiently problems can be solved on a model of computation, using an algorithm. The field is divided into three major branches: automata theory and language, computability theory, and computational complexity  An Introduction to Statistical Learning - Personal World Wide Web
Gareth James • Daniela Witten • Trevor Hastie. Robert Tibshirani. An Introduction to. Statistical Learning with Applications in R. 123 In practice, one can usuallycompute the training MSE with relative ease, but estimating test .. In theory wewould always like to predict qualitative responses using the.

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