Computer Science At Cambridge

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  computer science at cambridge: Cambridge International AS and A Level Computer Science Coursebook Sylvia Langfield, Dave Duddell, 2015-12-17 Cambridge International AS and A Level Computer Science Coursebook delivers an accessible guide to theoretical and practical skills in Computer Science, with a clear progression of tasks that help to consolidate and develop knowledge. Cambridge International AS and A Level Computer Science Coursebook offers students detailed descriptions of the concepts, reinforced with examples that outline complex subject matter in a clear way. Alongside fundamental definitions, higher level programming skills are developed through the explanation of processes and consolidated by practical exam-type questions for students to attempt.-- Publisher description.
  computer science at cambridge: Cambridge IGCSE Computer Science David Watson, Helen Williams, 2015-01-30 Endorsed by Cambridge Assessment International Education. Develop computational thinking and programming skills with complete coverage of the latest syllabus from experienced examiners and teachers. - Follows the order of the syllabus exactly, ensuring complete coverage - Introduces students to self-learning exercises, helping them learn how to use their knowledge in new scenarios - Accompanying animation files of the key concepts are available to download for free online. www.hoddereducation.co.uk/cambridgeextras-1 - Answers are available on the Teacher's CD. This book covers the IGCSE (0478), O Level (2210) and US IGCSE entry (0473) syllabuses, which are for first examination 2015. It may also be a useful reference for students taking the new Computer Science AS level course (9608).
  computer science at cambridge: Cambridge IGCSE® and O Level Computer Science Programming Book for Python Chris Roffey, 2017-02-02 This resource is written to follow the updated Cambridge IGCSE® Computer Science syllabus 0478 with examination from June and November 2016. Cambridge IGCSE® and O Level Computer Science Programming Book for Python accompanies the Cambridge IGCSE and O Level Computer Science coursebook, and is suitable for students and teachers wishing to use Python in their studies. It introduces and develops practical skills to guide students in developing coding solutions to the tasks presented in the book. Starting from simple skills and progressing to more complex challenges, this book shows how to approach a coding problem using Structure Diagrams and Flow Charts, explains programming logic using pseudocode, develops Python programming skills and gives full solutions to the tasks set.
  computer science at cambridge: Cambridge IGCSE® Computer Science Programming Book Richard Morgan, 2015-08-06 This resource is written to follow the updated Cambridge IGCSE® Computer Science syllabus 0478 with examination from June and November 2016.
  computer science at cambridge: Cambridge IGCSE® Computer Science Coursebook Sarah Lawrey, Donald Scott, 2015-11-12 This resource is written to follow the updated Cambridge IGCSE® Computer Science syllabus 0478 with examination from June and November 2016.
  computer science at cambridge: The Cambridge Handbook of Computing Education Research Sally A. Fincher, Anthony V. Robins, 2019-02-21 This Handbook describes the extent and shape of computing education research today. Over fifty leading researchers from academia and industry (including Google and Microsoft) have contributed chapters that together define and expand the evidence base. The foundational chapters set the field in context, articulate expertise from key disciplines, and form a practical guide for new researchers. They address what can be learned empirically, methodologically and theoretically from each area. The topic chapters explore issues that are of current interest, why they matter, and what is already known. They include discussion of motivational context, implications for practice, and open questions which might suggest future research. The authors provide an authoritative introduction to the field which is essential reading for policy makers, as well as both new and established researchers.
  computer science at cambridge: Design Theory and Computer Science Subrata Dasgupta, 1991-05-16 The author examines logic and methodology of design from the perspective of computer science. Computers provide the context for this examination both by discussion of the design process for hardware and software systems and by consideration of the role of computers in design in general. The central question posed by the author is whether or not we can construct a theory of design.
  computer science at cambridge: Cambridge International AS and A Level Computer Science Revision Guide Tony Piper, 2016-04-14 Cambridge International AS and A Level Computer Science offers a complete set of resources to accompany the 9608 syllabus. This revision guide helps students to prepare and practice skills for the Cambridge AS and A Level Computer Science examination. It contains clear explanations and key information to support learners, with additional practice questions to help students feel confident and reinforce their understanding of key concepts.
  computer science at cambridge: Categories and Computer Science R. F. C. Walters, Richard F. Walters, 1991 Category theory has become increasingly important and popular in computer science, and many universities now have introductions to category theory as part of their courses for undergraduate computer scientists. The author is a respected category theorist and has based this textbook on a course given over the last few years at the University of Sydney. The theory is developed in a straightforward way, and is enriched with many examples from computer science. Thus this book meets the needs of undergradute computer scientists, and yet retains a level of mathematical correctness that will broaden its appeal to include students of mathematics new to category theory.
  computer science at cambridge: Cambridge International AS & A Level Computer Science David Watson, Helen Williams, 2019-07-15 This title is endorsed by Cambridge Assessment International Education to support the full syllabus for examination from 2021. Develop computational thinking and ensure full coverage of the revised Cambridge Assessment International Education AS & A Level Computer Science syllabus (9618) with this comprehensive Student's Book written by experienced authors and examiners. - Improve understanding with clear explanations, examples, illustrations and diagrams, plus a glossary of key terms - Reinforce learning with a range of activities, exercises, and exam-style questions - Prepare for further study with extension activities that go beyond the requirements of the syllabus and prompt further investigation about new developments in technology - Follow a structured route through the course with in-depth coverage of the full AS & A Level syllabus - Answers are available online www.hoddereducation.co.uk/cambridgeextras Also available in the series Programming skills workbook ISBN: 9781510457683 Student eTextbook ISBN: 9781510457614 Whiteboard eTextbook ISBN: 9781510457621
  computer science at cambridge: Connecting Discrete Mathematics and Computer Science David Liben-Nowell, 2022-08-04 Computer science majors taking a non-programming-based course like discrete mathematics might ask 'Why do I need to learn this?' Written with these students in mind, this text introduces the mathematical foundations of computer science by providing a comprehensive treatment of standard technical topics while simultaneously illustrating some of the broad-ranging applications of that material throughout the field. Chapters on core topics from discrete structures – like logic, proofs, number theory, counting, probability, graphs – are augmented with around 60 'computer science connections' pages introducing their applications: for example, game trees (logic), triangulation of scenes in computer graphics (induction), the Enigma machine (counting), algorithmic bias (relations), differential privacy (probability), and paired kidney transplants (graphs). Pedagogical features include 'Why You Might Care' sections, quick-reference chapter guides and key terms and results summaries, problem-solving and writing tips, 'Taking it Further' asides with more technical details, and around 1700 exercises, 435 worked examples, and 480 figures.
  computer science at cambridge: Cambridge IGCSE and O Level Computer Science Second Edition David Watson, Helen Williams, 2021-04-16 This title is endorsed by Cambridge Assessment International Education to support the full syllabus for examination from 2023. Benefit from the knowledge of our renowned expert authors to navigate through the content of the updated Cambridge IGCSETM and O Level Computer Science syllabuses (0478/0984/2210). - Develop computational thinking and problem-solving skills: clearly-explained concepts are followed by opportunities to implement in the programming language of choice. - Build an understanding of computer systems and associated technologies: carefully prepared worked examples explain new ideas alongside activities to test and consolidate. - Navigate the syllabus confidently: supplementary subject content is flagged clearly, with introductions to each topic outlining the learning objectives. - Satisfy curiosity: students are encouraged to deepen their knowledge and understanding of the subject with Extension Activities and Find Out More. - Consolidate skills and check understanding: self-assessment questions, activities and exam-style questions are embedded throughout the book, alongside key definitions of technical terms and a glossary. Answers to the Student Book are available in Cambridge IGCSE and O Level Computer Science Teacher's Guide with Boost Subscription 9781398318502
  computer science at cambridge: How to Think Like a Mathematician Kevin Houston, 2009-02-12 Looking for a head start in your undergraduate degree in mathematics? Maybe you've already started your degree and feel bewildered by the subject you previously loved? Don't panic! This friendly companion will ease your transition to real mathematical thinking. Working through the book you will develop an arsenal of techniques to help you unlock the meaning of definitions, theorems and proofs, solve problems, and write mathematics effectively. All the major methods of proof - direct method, cases, induction, contradiction and contrapositive - are featured. Concrete examples are used throughout, and you'll get plenty of practice on topics common to many courses such as divisors, Euclidean algorithms, modular arithmetic, equivalence relations, and injectivity and surjectivity of functions. The material has been tested by real students over many years so all the essentials are covered. With over 300 exercises to help you test your progress, you'll soon learn how to think like a mathematician.
  computer science at cambridge: C by Example Noel Kalicharan, 1994-09-15 C is one of the most popular programming languages today. It is flexible, efficient and highly portable, and is used for writing many different kinds of programs, from compilers and assemblers to spreadsheets and games. This book is based on ANSI C - the recently adopted standard for the C language. It assumes familiarity with basic programming concepts such as variables, constants, iteration and looping, but covers all aspects of C. In general it is as much about learning programming skills as it is about mastering the art of coding programs in C. To this end the text contains a wealth of examples and exercises that foster and test the understanding of the concepts developed in each chapter. An outstanding feature of this book is a treatment of 'pointers'. The topic is presented in a clear, logical and reasoned manner that is easy to follow. Binary files and random access files are also treated in such a manner that the reader can easily become adept at using them. Anybody who wishes to get to grips with the art of programming in C will find this a most valuable book.
  computer science at cambridge: Logic in Computer Science Michael Huth, Mark Ryan, 2004-08-26 Provides a sound basis in logic, and introduces logical frameworks used in modelling, specifying and verifying computer systems.
  computer science at cambridge: Cambridge IGCSE® Computer Science Revision Guide David Watson, Helen Williams, 2015-09-03 Cambridge IGCSE Computer Science Revision Guide follows the Cambridge IGCSE (0478) and Cambridge O Level (2210) Computer Science syllabuses, matching the syllabus for examination from 2015. The book instils confidence and thorough understanding of the topics learned by the students as they revise for examinations, and is written in a clear and straightforward tone to assist learning concepts and theories. This revision guide is endorsed by Cambridge International Examinations.
  computer science at cambridge: From Semantics to Computer Science Gilles Kahn, Yves Bertot, 2009-09-24 Gilles Kahn was one of the most influential figures in the development of computer science and information technology, not only in Europe but throughout the world. This volume of articles by several leading computer scientists serves as a fitting memorial to Kahn's achievements and reflects the broad range of subjects to which he contributed through his scientific research and his work at INRIA, the French National Institute for Research in Computer Science and Control. The authors also reflect upon the future of computing: how it will develop as a subject in itself and how it will affect other disciplines, from biology and medical informatics, to web and networks in general. Its breadth of coverage, topicality, originality and depth of contribution, make this book a stimulating read for all those interested in the future development of information technology.
  computer science at cambridge: The Principles of Computer Networking D. Russell, 1989-11-16 This 1989 book provides an introduction to the immensely important area of computer networking.
  computer science at cambridge: The Pleasures of Counting T. W. Körner, 1996-12-05 What is the connection between the outbreak of cholera in Victorian Soho, the Battle of the Atlantic, African Eve and the design of anchors? One answer is that they are all examples chosen by Dr Tom Körner to show how a little mathematics can shed light on the world around us, and deepen our understanding of it. Dr Körner, an experienced author, describes a variety of topics which continue to interest professional mathematicians, like him. He does this using relatively simple terms and ideas, yet confronting difficulties (which are often the starting point for new discoveries) and avoiding condescension. If you have ever wondered what it is that mathematicians do, and how they go about it, then read on. If you are a mathematician wanting to explain to others how you spend your working days (and nights), then seek inspiration here.
  computer science at cambridge: Logic and Computation Lawrence C. Paulson, 1987 This book is concerned with techniques for formal theorem-proving, with particular reference to Cambridge LCF (Logic for Computable Functions). Cambridge LCF is a computer program for reasoning about computation. It combines the methods of mathematical logic with domain theory, the basis of the denotational approach to specifying the meaning of program statements. Cambridge LCF is based on an earlier theorem-proving system, Edinburgh LCF, which introduced a design that gives the user flexibility to use and extend the system. A goal of this book is to explain the design, which has been adopted in several other systems. The book consists of two parts. Part I outlines the mathematical preliminaries, elementary logic and domain theory, and explains them at an intuitive level, giving reference to more advanced reading; Part II provides sufficient detail to serve as a reference manual for Cambridge LCF. It will also be a useful guide for implementors of other programs based on the LCF approach.
  computer science at cambridge: A/AS Level Computer Science for OCR Student Book Alistair Surrall, Adam Hamflett, 2017-10-05 Written for the OCR A/AS Level Computer Science specifications for first teaching from 2015, this print student book helps students build their knowledge and master underlying computing principles and concepts. The student book develops computational thinking, programming and problem-solving skills. Suitable for all abilities, it puts computing into context and gives students a real-life view on professional applications of computing skills. Answers to end-of-chapter questions are located in the free online teacher's resource. A Cambridge Elevate enhanced edition is also available.
  computer science at cambridge: Cambridge IGCSE Computer Science Study and Revision Guide David Watson, Helen Williams, 2016-07-29 Providing guidance that helps students practice and troubleshoot their exam technique,these books send them into their exam with the confidence to aim for the best grades. - Enables students to avoid common misconceptions and mistakes by highlighting them throughout - Builds students' skills constructing and writing answers as they progress through a range of practice questions - Allows students to mark their own responses and easily identify areas for improvement using the answers in the back of the book - Helps students target their revision and focus on important concepts and skills with key objectives at the beginning of every chapter - Ensures that students maximise their time in the exam by including examiner's tops and suggestions on how to approach the questions This title has not been through the Cambridge International Examinations endorsement process.
  computer science at cambridge: Basic Computation and Programming with C Subrata Saha, Subhodip Mukherjee, 2017-01-16 Providing in-depth coverage, this book covers the fundamentals of computation and programming in C language. Essential concepts including operators and expressions, input and output statements, loop statements, arrays, pointers, functions, strings and preprocessors are described in a lucid manner. A unique approach - 'Learn by quiz' - features questions based on confidence-based learning methodology. It helps the reader to identify the right answer with adequate explanation and reasoning as to why the other options are incorrect. Computer programs and review questions are interspersed throughout the text. The book is appropriate for undergraduate students of engineering, computer science and information technology. It can be used for self-study and assists in the understanding of theoretical concepts and their applications.
  computer science at cambridge: A First Course in Network Science Filippo Menczer, Santo Fortunato, Clayton A. Davis, 2020-01-30 Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.
  computer science at cambridge: Epistemic Logic for AI and Computer Science J.-J. Ch. Meyer, John-Jules Ch Meyer, W. van der Hoek, 2004-03-25 A broad introduction to the subject; many exercises with full solutions are provided.
  computer science at cambridge: Computer Science Education Research Sally Fincher, Marian Petre, 2004-01-01 This book provides an overview of how to approach computer science education research from a pragmatic perspective. It represents the diversity of traditions and approaches inherent in this interdisciplinary area, while also providing a structure within which to make sense of that diversity. It provides multiple 'entry points'- to literature, to methods, to topics Part One, 'The Field and the Endeavor', frames the nature and conduct of research in computer science education. Part Two, 'Perspectives and Approaches', provides a number of grounded chapters on particular topics or themes, written by experts in each domain. These chapters cover the following topics: * design * novice misconceptions * programming environments for novices * algorithm visualisation * a schema theory view on learning to program * critical theory as a theoretical approach to computer science education research Juxtaposed and taken together, these chapters indicate just how varied the perspectives and research approaches can be. These chapters, too, act as entry points, with illustrations drawn from published work.
  computer science at cambridge: Concepts in Programming Languages John C. Mitchell, 2003 A comprehensive undergraduate textbook covering both theory and practical design issues, with an emphasis on object-oriented languages.
  computer science at cambridge: Categories and Computer Science Richard F. Walters, 1991
  computer science at cambridge: OCaml from the Very Beginning John Whitington, 2013 In OCaml from the Very Beginning John Whitington takes a no-prerequisites approach to teaching a modern general-purpose programming language. Each small, self-contained chapter introduces a new topic, building until the reader can write quite substantial programs. There are plenty of questions and, crucially, worked answers and hints. OCaml from the Very Beginning will appeal both to new programmers, and experienced programmers eager to explore functional languages such as OCaml. It is suitable both for formal use within an undergraduate or graduate curriculum, and for the interested amateur.
  computer science at cambridge: Artificial Unintelligence Meredith Broussard, 2019-01-29 A guide to understanding the inner workings and outer limits of technology and why we should never assume that computers always get it right. In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally—hiring, driving, paying bills, even choosing romantic partners—that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology. With this book, she offers a guide to understanding the inner workings and outer limits of technology—and issues a warning that we should never assume that computers always get things right. Making a case against technochauvinism—the belief that technology is always the solution—Broussard argues that it's just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding “the cyborg future is not coming any time soon”; uses artificial intelligence to investigate why students can't pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone.
  computer science at cambridge: Turing's Vision Chris Bernhardt, 2016-05-13 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.
  computer science at cambridge: Scientific Programming Jorge Alberto Calvo, 2018-12-19 This book offers an introduction to computer programming, numerical analysis, and other mathematical ideas that extend the basic topics learned in calculus. It illustrates how mathematicians and scientists write computer programs, covering the general building blocks of programming languages and a description of how these concepts fit together to allow computers to produce the results they do. Topics explored here include binary arithmetic, algorithms for rendering graphics, the smooth interpolation of discrete data, and the numerical approximation of non-elementary integrals. The book uses an open-source computer algebra system called Maxima. Using Maxima, first-time programmers can perform familiar tasks, such as graphing functions or solving equations, and learn the basic structures of programming before moving on to other popular programming languages. The epilogue provides some simple examples of how this process works in practice. The book will particularly appeal to students who have finished their calculus sequence.
  computer science at cambridge: A/AS Level Computer Science for WJEC/Eduqas Student Book Mark Thomas, Alistair Surrall, Adam Hamflett, 2017-10-05 Written for the WJEC/Eduqas A/AS Level Computer Science specifications for first teaching from 2015, this print student book helps students build their knowledge and master underlying computing principles and concepts. The student book develops computational thinking, programming and problem-solving skills. Suitable for all abilities, it puts computing into context and gives students a real-life view on professional applications of computing skills. Answers to end-of-chapter questions are located in the free online teacher's resource. A Cambridge Elevate enhanced edition is also available.
  computer science at cambridge: How to Design Programs, second edition Matthias Felleisen, Robert Bruce Findler, Matthew Flatt, Shriram Krishnamurthi, 2018-05-25 A completely revised edition, offering new design recipes for interactive programs and support for images as plain values, testing, event-driven programming, and even distributed programming. This introduction to programming places computer science at the core of a liberal arts education. Unlike other introductory books, it focuses on the program design process, presenting program design guidelines that show the reader how to analyze a problem statement, how to formulate concise goals, how to make up examples, how to develop an outline of the solution, how to finish the program, and how to test it. Because learning to design programs is about the study of principles and the acquisition of transferable skills, the text does not use an off-the-shelf industrial language but presents a tailor-made teaching language. For the same reason, it offers DrRacket, a programming environment for novices that supports playful, feedback-oriented learning. The environment grows with readers as they master the material in the book until it supports a full-fledged language for the whole spectrum of programming tasks. This second edition has been completely revised. While the book continues to teach a systematic approach to program design, the second edition introduces different design recipes for interactive programs with graphical interfaces and batch programs. It also enriches its design recipes for functions with numerous new hints. Finally, the teaching languages and their IDE now come with support for images as plain values, testing, event-driven programming, and even distributed programming.
  computer science at cambridge: The Quest for Artificial Intelligence Nils J. Nilsson, 2009-10-30 Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.
  computer science at cambridge: Quantum Computer Science N. David Mermin, 2007-08-30 In the 1990's it was realized that quantum physics has some spectacular applications in computer science. This book is a concise introduction to quantum computation, developing the basic elements of this new branch of computational theory without assuming any background in physics. It begins with an introduction to the quantum theory from a computer-science perspective. It illustrates the quantum-computational approach with several elementary examples of quantum speed-up, before moving to the major applications: Shor's factoring algorithm, Grover's search algorithm, and quantum error correction. The book is intended primarily for computer scientists who know nothing about quantum theory, but will also be of interest to physicists who want to learn the theory of quantum computation, and philosophers of science interested in quantum foundational issues. It evolved during six years of teaching the subject to undergraduates and graduate students in computer science, mathematics, engineering, and physics, at Cornell University.
  computer science at cambridge: Deep Learning Ian Goodfellow, Yoshua Bengio, Aaron Courville, 2016-11-10 An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
  computer science at cambridge: Computational Thinking Peter J. Denning, Matti Tedre, 2019-05-14 This pocket-sized introduction to computational thinking and problem-solving traces its genealogy centuries before the digital computer. A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation. Eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, “computational thinking” has become part of the K–12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview—tracing a genealogy that begins centuries before digital computers and portraying computational thinking as the pioneers of computing have described it. The authors explain that computational thinking (CT) is not a set of concepts for programming; it is a way of thinking that is honed through practice: the mental skills for designing computations to do jobs for us, and for explaining and interpreting the world as a complex of information processes. Mathematically trained experts (known as “computers”) who performed complex calculations as teams engaged in CT long before electronic computers. In each chapter, the author identify different dimensions of today's highly developed CT: • Computational Methods • Computing Machines • Computing Education • Software Engineering • Computational Science • Design Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.
  computer science at cambridge: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
  computer science at cambridge: The Turing Omnibus A. K. Dewdney, 1989
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A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …

Computer | Definition, History, Operating Systems, & Facts
A computer is a programmable device for processing, storing, and displaying information. Learn more in this article about modern digital electronic computers and their design, constituent …

What is a Computer?
Feb 6, 2025 · What is a Computer? A computer is a programmable device that stores, retrieves, and processes data. The term "computer" was originally given to humans (human computers) …

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What is a Computer? - GeeksforGeeks
Apr 7, 2025 · A computer is an electronic device that processes, stores, and executes instructions to perform tasks. It includes key components such as the CPU (Central Processing Unit), RAM …

Computer Basics: What is a Computer? - GCFGlobal.org
What is a computer? A computer is an electronic device that manipulates information, or data. It has the ability to store, retrieve, and process data. You may already know that you can use a …

What is a Computer? (Definition & Meaning) - Webopedia
Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …

Computer - Simple English Wikipedia, the free encyclopedia
A computer is a machine that uses electronics to input, process, store, and output data. Data is information such as numbers, words, and lists. Input of data means to read information from a …

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What is Computer? Definition, Characteristics and Classification
Aug 7, 2024 · A computer is an electronic device wherein we need to input raw data to be processed with a set of programs to produce a desirable output. Computers have the ability to …