A walkthrough of computer science concepts you must know. Designed for readers who don't care for academic formalities, it's a fast and easy computer science guide. It teaches the foundations you need to program computers effectively. After a simple introduction to discrete math, it presents common algorithms and data structures. It also outlines the principles that make computers and programming languages work.
What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of the new and familiar is the most fulfilling? These may seem like uniquely human quandaries, but they are not. Computers, like us, confront limited space and time, so computer scientists have been grappling with similar problems for decades. And the solutions theyâve found have much to teach us.
In a dazzlingly interdisciplinary work, Brian Christian and Tom Griffiths show how algorithms developed for computers also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing oneâs inbox to peering into the future, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.
Robert Sedgewick and Kevin WayneâsÂ Computer Science: An Interdisciplinary Approach Â is the ideal modern introduction to computer science with Java programming for both students and professionals. Taking a broad, applications-based approach, Sedgewick and Wayne teach through important examples from science, mathematics, engineering, finance, and commercial computing.
The book demystifies computation, explains its intellectual underpinnings, and covers the essential elements of programming and computational problem solving in todayâs environments. The authors begin by introducing basic programming elements such as variables, conditionals, loops, arrays, and I/O. Next, they turn to functions, introducing key modular programming concepts, including components and reuse. They present a modern introduction to object-oriented programming, covering current programming paradigms and approaches to data abstraction.
Building on this foundation, Sedgewick and Wayne widen their focus to the broader discipline of computer science. They introduce classical sorting and searching algorithms, fundamental data structures and their application, and scientific techniques for assessing an implementationâs performance. Using abstract models, readers learn to answer basic questions about computation, gaining insight for practical application. Finally, the authors show how machine architecture links the theory of computing to real computers, and to the fieldâs history and evolution.
For each concept, the authors present all the information readers need to build confidence, together with examples that solve intriguing problems. Each chapter contains question-and-answer sections, self-study drills, and challenging problems that demand creative solutions.
Companion web siteÂ (introcs.cs.princeton.edu/java) contains
Companion 20-part series of video lecturesÂ is available atÂ informit.com/title/9780134493831
The Evolution of Technology
Having sold more than 2 million copies over its lifetime, How Computers Work is the definitive illustrated guide to the world of PCs and technology. In this new edition, youâll find detailed information not just about PCs, but about how changes in technology have evolved the giant, expensive computer dinosaurs of last century into the smaller but more powerful smartphones, tablets, and wearable computing of today. Whether your interest is in business, gaming, digital photography, entertainment, communications, or security, youâll learn how computing is evolving the way you live.
A full-color, illustrated adventure into the wonders of TECHNOLOOGY
This full-color, fully illustrated guide to the world of technology assumes nothing and explains everything. Only the accomplished and award-winning team of writer Ron White and artist Tim Downs has the unique ability to meld descriptive text with one-of-a-kind visuals to fully explain how the electronic gear we depend on every day is made possible. In addition to all the content youâve come to expect from prior editions, this newly revised edition includes all-new coverage of topics such as:
â¢Â Â How smartphones and tablet PCs put the power of a desktop computer in your handsâliterally
â¢Â Â How computing technology is linking our homes, work place, entertainment, and daily communications
â¢Â Â How advances such as Facebook, Twitter, Google, eBay, and smartphones are expanding our universe of friends, knowledge, and opportunity
â¢Â Â How increased miniaturization leads to new products, such as smartphone, smartwatches, and Google Glass
â¢Â Â How computing technology takes advantages of quantum physics and innovations no one even imagined a few years ago
For two decades, How Computers Work has helped newbies understand new technology, while hackers and IT pros have treasured it for the depth of knowledge it contains. This is the perfect book about computing to capture your imagination, delight your eyes, and expand your mind, no matter what your technical level!
Beautifully detailed illustrations and jargon-free explanations walk you through the technology that is shaping our lives. See the hidden workings inside computers, smartphones, tablets, Google Glass, and the latest tech inventions.
Computer Science: An Overview is intended for use in the Introduction to Computer Science course. It is also suitable for all readers interested in a breadth-first introduction to computer science.
Computer Science uses broad coverage and clear exposition to present a complete picture of the dynamic computer science field. Accessible to students from all backgrounds, Glenn Brookshear and Dennis Brylow encourage the development of a practical, realistic understanding of the field. An overview of each of the important areas of Computer Science provides students with a general level of proficiency for future courses. This new edition incorporates an introduction to the Python programming language into key chapters.
Teaching and Learning Experience
This program will provide a better teaching and learning experienceâfor you and your students. It will help:
Turing's fascinating and remarkable theory, which now forms the basis of computer science, explained for the general reader.
In 1936, when he was just twenty-four years old, Alan Turing wrote a remarkable paper in which he outlined the theory of computation, laying out the ideas that underlie all modern computers. This groundbreaking and powerful theory now forms the basis of computer science. In Turing's Vision, Chris Bernhardt explains the theory, Turing's most important contribution, for the general reader. Bernhardt argues that the strength of Turing's theory is its simplicity, and that, explained in a straightforward manner, it is eminently understandable by the nonspecialist. As Marvin Minsky writes, "The sheer simplicity of the theory's foundation and extraordinary short path from this foundation to its logical and surprising conclusions give the theory a mathematical beauty that alone guarantees it a permanent place in computer theory." Bernhardt begins with the foundation and systematically builds to the surprising conclusions. He also views Turing's theory in the context of mathematical history, other views of computation (including those of Alonzo Church), Turing's later work, and the birth of the modern computer.
In the paper, "On Computable Numbers, with an Application to the Entscheidungsproblem," Turing thinks carefully about how humans perform computation, breaking it down into a sequence of steps, and then constructs theoretical machines capable of performing each step. Turing wanted to show that there were problems that were beyond any computer's ability to solve; in particular, he wanted to find a decision problem that he could prove was undecidable. To explain Turing's ideas, Bernhardt examines three well-known decision problems to explore the concept of undecidability; investigates theoretical computing machines, including Turing machines; explains universal machines; and proves that certain problems are undecidable, including Turing's problem concerning computable numbers.
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