Download or read book Demystifying Computation A Hands on Introduction written by Apostolos Syropoulos and published by World Scientific Publishing Company. This book was released on 2017-04-19 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Problem solving in computing is referred to as computational thinking. The theory behind this concept is challenging in its technicalities, yet simple in its ideas. This book introduces the theory of computation from its inception to current form of complexity; from explanations of how the field of computer science was formed using classical ideas in mathematics by Gödel, to conceptualization of the Turing Machine, to its more recent innovations in quantum computation, hypercomputation, vague computing and natural computing. It describes the impact of these in relation to academia, business and wider society, providing a sound theoretical basis for its practical application.Written for accessibility, Demystifying Computation provides the basic knowledge needed for non-experts in the field, undergraduate computer scientists and students of information and communication technology and software development.
Download or read book Unravelling Complexity The Life And Work Of Gregory Chaitin written by Shyam Wuppuluri and published by World Scientific. This book was released on 2020-02-06 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: The revolutions that Gregory Chaitin brought within the fields of science are well known. From his discovery of algorithmic information complexity to his work on Gödel's theorem, he has contributed deeply and expansively to such diverse fields.This book attempts to bring together a collection of articles written by his colleagues, collaborators and friends to celebrate his work in a festschrift. It encompasses various aspects of the scientific work that Chaitin has accomplished over the years. Topics range from philosophy to biology, from foundations of mathematics to physics, from logic to computer science, and all other areas Chaitin has worked on.It also includes sketches of his personality with the help of biographical accounts in some unconventional articles that will provide a rare glimpse into the personal life and nature of Chaitin.Compared to the other books that exist along a similar vein, this book stands out primarily due to its highly interdisciplinary nature and its scope that will attract readers into Chaitin's world.
Download or read book Encyclopedia of Information Science and Technology Fifth Edition written by Khosrow-Pour D.B.A., Mehdi and published by IGI Global. This book was released on 2020-07-24 with total page 1966 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rise of intelligence and computation within technology has created an eruption of potential applications in numerous professional industries. Techniques such as data analysis, cloud computing, machine learning, and others have altered the traditional processes of various disciplines including healthcare, economics, transportation, and politics. Information technology in today’s world is beginning to uncover opportunities for experts in these fields that they are not yet aware of. The exposure of specific instances in which these devices are being implemented will assist other specialists in how to successfully utilize these transformative tools with the appropriate amount of discretion, safety, and awareness. Considering the level of diverse uses and practices throughout the globe, the fifth edition of the Encyclopedia of Information Science and Technology series continues the enduring legacy set forth by its predecessors as a premier reference that contributes the most cutting-edge concepts and methodologies to the research community. The Encyclopedia of Information Science and Technology, Fifth Edition is a three-volume set that includes 136 original and previously unpublished research chapters that present multidisciplinary research and expert insights into new methods and processes for understanding modern technological tools and their applications as well as emerging theories and ethical controversies surrounding the field of information science. Highlighting a wide range of topics such as natural language processing, decision support systems, and electronic government, this book offers strategies for implementing smart devices and analytics into various professional disciplines. The techniques discussed in this publication are ideal for IT professionals, developers, computer scientists, practitioners, managers, policymakers, engineers, data analysts, and programmers seeking to understand the latest developments within this field and who are looking to apply new tools and policies in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to software engineering, cybersecurity, information technology, media and communications, urban planning, computer science, healthcare, economics, environmental science, data management, and political science will benefit from the extensive knowledge compiled within this publication.
Download or read book Computational Thinking A Perspective on Computer Science written by Zhiwei Xu and published by Springer Nature. This book was released on 2022-01-01 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is intended as a textbook for one-semester, introductory computer science courses aimed at undergraduate students from all disciplines. Self-contained and with no prerequisites, it focuses on elementary knowledge and thinking models. The content has been tested in university classrooms for over six years, and has been used in summer schools to train university and high-school teachers on teaching introductory computer science courses using computational thinking. This book introduces computer science from a computational thinking perspective. In computer science the way of thinking is characterized by three external and eight internal features, including automatic execution, bit-accuracy and abstraction. The book is divided into chapters on logic thinking, algorithmic thinking, systems thinking, and network thinking. It also covers societal impact and responsible computing material – from ICT industry to digital economy, from the wonder of exponentiation to wonder of cyberspace, and from code of conduct to best practices for independent work. The book’s structure encourages active, hands-on learning using the pedagogic tool Bloom's taxonomy to create computational solutions to over 200 problems of varying difficulty. Students solve problems using a combination of thought experiment, programming, and written methods. Only 300 lines of code in total are required to solve most programming problems in this book.
Download or read book Introduction to Computational Thinking written by Thomas Mailund and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn approaches of computational thinking and the art of designing algorithms. Most of the algorithms you will see in this book are used in almost all software that runs on your computer. Learning how to program can be very rewarding. It is a special feeling to seeing a computer translate your thoughts into actions and see it solve your problems for you. To get to that point, however, you must learn to think about computations in a new way-you must learn computational thinking. This book begins by discussing models of the world and how to formalize problems. This leads onto a definition of computational thinking and putting computational thinking in a broader context. The practical coding in the book is carried out in Python; you'll get an introduction to Python programming, including how to set up your development environment. You will: Think in a computational way Acquire general techniques for problem solving See general and concrete algorithmic techniques Program solutions that are both computationally efficient and maintainable.
Download or read book Essential Computational Thinking written by Ricky J. Sethi and published by Cognella Academic Publishing. This book was released on 2020-06-17 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essential Computational Thinking: Computer Science from Scratch helps students build a theoretical and practical foundation for learning computer science. Rooted in fundamental science, this text defines elementary ideas including data and information, quantifies these ideas mathematically, and, through key concepts in physics and computation, demonstrates the relationship between computer science and the universe itself. In Part I, students explore the theoretical underpinnings of computer science in a wide-ranging manner. Readers receive a robust overview of essential computational theories and programming ideas, as well as topics that examine the mathematical and physical foundations of computer science. Part 2 presents the basics of computation and underscores programming as an invaluable tool in the discipline. Students can apply their newfound knowledge and begin writing substantial programs immediately. Finally, Part 3 explores more sophisticated computational ideas, including object-oriented programing, databases, data science, and some of the underlying principles of machine learning. Essential Computational Thinking is an ideal text for a firmly technical CS0 course in computer science. It is also a valuable resource for highly-motivated non-computer science majors at the undergraduate or graduate level who are interested in learning more about the discipline for either professional or personal development.
Download or read book Computational Thinking written by Peter J. Denning and published by MIT Press. This book was released on 2019-05-14 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to computational thinking that traces a genealogy beginning 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 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. The authors identify six dimensions of today's highly developed CT—methods, machines, computing education, software engineering, computational science, and design—and cover each in a chapter. Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.
Download or read book Theory of Computing written by Efim Kinber and published by Pearson. This book was released on 2001 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Appropriate for upper division undergraduate and graduate level courses in Computer Science Theory, Theory of Computation, and Automata and Formal Language Theory. This book focuses on fundamental issues of computation. The readers can master the content and gain lasting perspective from which to understand computers by carefully worked out examples, illustrations, and algorithmic proofs. It is especially appropriate for one-term courses.
Download or read book Introduction to the Theory of Computation written by Michael Sipser and published by Cengage Learning. This book was released on 2005-02-15 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly anticipated revision builds upon the strengths of the previous edition. Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Download or read book An Introduction to the Theory of Computation written by Eitan M. Gurari and published by . This book was released on 1989 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Computation in Physical Sciences written by Jay Wang and published by Springer. This book was released on 2023-01-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a practical and comprehensive introduction to computational problem solving from the viewpoints of practitioners in both academic and industrial worlds. The authors present scientific problem-solving using computation and aim to increase computational thinking, which is the mindset and skillset required to solve scientific problems with computational methodologies via model building, simulation, data analysis, and visualization using the Python programming language. Topics and examples span fundamental areas of physical science as well as contemporary topics including quantum computing, neural networks, machine learning, global warming, and energy balance. The book features unique and innovative techniques and practices including: intentional scaffolding to help beginners learn computational problem solving; multimodal computing environments including cloud-based platforms and just-in-time computing; emphasis and connection between both numerical and symbolic computations; and extensive exercise sets carefully designed for further exploration as project assignments or self-paced study. The book is suitable for introductory level readers in physical sciences, engineering, and related STEM disciplines. Specifically, the book is appropriate for use in either a standalone course on computation and modeling and as a resource for readers interested in learning about proven techniques in interactive computing.
Download or read book Theory of Computation written by James L. Hein and published by Jones & Bartlett Pub. This book was released on 1996-01 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Programs and Machines written by Richard Bird and published by . This book was released on 1976 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Theory of Computing written by Efim Kinber and published by Prentice Hall. This book was released on 2000-01 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Classical and Quantum Computing written by Thomas Wong and published by . This book was released on 2022-01-21 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Cambridge Handbook of Computing Education Research written by Sally A. Fincher and published by . This book was released on 2019-02-13 with total page 924 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an authoritative introduction to Computing Education research written by over 50 leading researchers from academia and the industry.
Download or read book Demystifying Deep Learning written by Douglas J. Santry and published by John Wiley & Sons. This book was released on 2023-12-12 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how to train Deep Learning models by learning how to build real Deep Learning software libraries and verification software! The study of Deep Learning and Artificial Neural Networks (ANN) is a significant subfield of artificial intelligence (AI) that can be found within numerous fields: medicine, law, financial service, and science, for example. Just as the robot revolution threatened blue-collar jobs in the 1970s, so now the AI revolution promises a new era of productivity for white collar jobs. Important tasks have begun being taken over by ANNs, from disease detection and prevention to reading and supporting legal contracts, to understanding experimental data, model protein folding, and hurricane modeling. AI is everywhere—on the news, in think tanks, and occupies government policy makers all over the world —and ANNs often provide the backbone for AI. Relying on an informal and succinct approach, Demystifying Deep Learning is a useful tool to learn the necessary steps to implement ANN algorithms by using both a software library applying neural network training and verification software. The volume offers explanations of how real ANNs work, and includes 6 practical examples that demonstrate in real code how to build ANNS and the datasets they need in their implementation, available in open-source to ensure practical usage. This approachable book follows ANN techniques that are used every day as they adapt to natural language processing, image recognition, problem solving, and generative applications. This volume is an important introduction to the field equipping the reader for more advanced study. Demystifying Deep Learning readers will also find: A volume that emphasizes the importance of classification Discussion of why ANN libraries (such as Tensor Flow and Pytorch) are written in C++ rather than Python Each chapter concludes with a “Projects” page to promote students experimenting with real code A supporting library of software to accompany the book at https://github.com/nom-de-guerre/RANT Approachable explanation of how generative AI, such as generative adversarial networks (GAN) really work. An accessible motivation and elucidation of how transformers, the basis of large language models (LLM) such as ChatGPT, work. Demystifying Deep Learning is ideal for engineers and professionals that need to learn and understand ANNs in their work. It is also a helpful text for advanced undergraduates to get a solid grounding on the topic.
