This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    Written By Two Of Today'S Most Respected Computer Science Educators, Nell Dale And John Lewis, The Text Provides A Broad Overview Of The Many Aspects Of The Discipline From A Generic View Point. Separate Program Language Chapters Are Available As Bundle Items For Those Instructors Who Would Like To Explore A Particular Programming Language With Their Students. The Many Layers Of Computing Are Thoroughly Explained Beginning With The Information Layer, Working Through The Hardware, Programming, Operating Systems, Application, And Communication Layers, And Ending With A Discussion On The Limitations Of Computing. Perfect For Introductory Computing And Computer Science Courses, Computer Science Illuminated, Third Edition's Thorough Presentation Of Computing Systems Provides Computer Science Majors With A Solid Foundation For Further Study, And Offers Non-Majors A Comprehensive And Complete Introduction To Computing.

    His Incompleteness Theorem turned not only mathematics but also the whole world of science and philosophy on its head. Equally legendary were Gö's eccentricities, his close friendship with Albert Einstein, and his paranoid fear of germs that eventually led to his death from self-starvation. Now, in the first popular biography of this strange and brilliant thinker, John Casti and Werner DePauli bring the legend to life. After describing his childhood in the Moravian capital of Brno, the authors trace the arc of Gö's remarkable career, from the famed Vienna Circle, where philosophers and scientists debated notions of truth, to the Institute for Advanced Study in Princeton, New Jersey, where he lived and worked until his death in 1978. In the process, they shed light on Gö's contributions to mathematics, philosophy, computer science, artificial intelligence -- even cosmology -- in an entertaining and accessible way.

    This process of “self-organization” reveals itself in the inanimate worlds of crystals and seashells, but as Len Fisher shows, it is also evident in living organisms, from fish to ants to human beings. The coordinated movements of fish in shoals, for example, arise from the simple rule: “Follow the fish in front.” Traffic flow arises from simple rules: “Keep your distance” and “Keep to the right.”Now, in his new book, Fisher shows how we can manage our complex social lives in an ever more chaotic world. His investigation encompasses topics ranging from “swarm intelligence” to the science of parties and the best ways to start a fad. Finally, Fisher sheds light on the beauty and utility of complexity theory. An entertaining journey into the science of everyday life, The Perfect Swarm will delight anyone who wants to understand the complex situations in which we so often find ourselves.

    The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout. Author resource page: http: //www.stat.columbia.edu/ gelman/arm/

    The heart of this creative process lies in an analogy between proving mathematical theorems by induction and designing combinatorial algorithms. The book contains hundreds of problems and examples. It is designed to enhance the reader's problem-solving abilities and understanding of the principles behind algorithm design.

    Republished in book form shortly thereafter, it has since gone through four hardcover and sixteen paperback printings. It is a revolutionary work, astounding in its foresight and contemporaneity. The University of Illinois Press is pleased and honored to issue this commemorative reprinting of a classic.

    He was forced to choose which path he was going to take: continue the cycle of family poverty or break it. The Mindset is an inspirational memoir of Ace Bowers’ personal transformation from janitor to millionaire. Bowers began his journey uneducated, overweight, addicted to cigarettes, in debt, and depressed. Revealing the skeletons in his closet for the first time set the scene for how he got to the point of cleaning a motel for $6 an hour. Bowers’ detailed accounts of his turbulent and traumatizing childhood illustrated what it is like growing up in a poor, alcoholic, and abusive family. The metamorphosis began as soon as he changed his mindset. Within five years, Bowers was able to completely turn his life around, going from trash to technology. This memoir illuminates step by step his unconventional path to wealth, health, and happiness.

    Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.

    

    The Windows Command Line Beginner's Guide gives users new to the Windows command line an overview of the Command Prompt, from simple tasks to network configuration.In the Guide, you'll learn how to:-Manage the Command Prompt.-Copy & paste from the Windows Command Prompt.-Create batch files.-Remotely manage Windows machines from the command line.-Manage disks, partitions, and volumes.-Set an IP address and configure other network settings.-Set and manage NTFS and file sharing permissions.-Customize and modify the Command Prompt.-Create and manage file shares.-Copy, move, and delete files and directories from the command line.-Manage PDF files and office documents from the command line.-And many other topics.

    It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.

    Introduction to Modern Cryptography provides a rigorous yet accessible treatment of modern cryptography, with a focus on formal definitions, precise assumptions, and rigorous proofs.The authors introduce the core principles of modern cryptography, including the modern, computational approach to security that overcomes the limitations of perfect secrecy. An extensive treatment of private-key encryption and message authentication follows. The authors also illustrate design principles for block ciphers, such as the Data Encryption Standard (DES) and the Advanced Encryption Standard (AES), and present provably secure constructions of block ciphers from lower-level primitives. The second half of the book focuses on public-key cryptography, beginning with a self-contained introduction to the number theory needed to understand the RSA, Diffie-Hellman, El Gamal, and other cryptosystems. After exploring public-key encryption and digital signatures, the book concludes with a discussion of the random oracle model and its applications.Serving as a textbook, a reference, or for self-study, Introduction to Modern Cryptography presents the necessary tools to fully understand this fascinating subject.

    More than 250 challenging practice questions have been completely revised to closely model the format, tone, topics, and difficulty of the real exam. An integrated study system based on proven pedagogy, exam coverage includes step-by-step exercises, special Exam Watch notes, On-the-Job elements, and Self Tests with in-depth answer explanations to help reinforce and teach practical skills.Praise for the author:"Finally A Java certification book that explains everything clearly. All you need to pass the exam is in this book."--Solveig Haugland, Technical Trainer and Former Sun Course Developer"Who better to write a Java study guide than Kathy Sierra, the reigning queen of Java instruction? Kathy Sierra has done it again--here is a study guide that almost guarantees you a certification "--James Cubeta, Systems Engineer, SGI"The thing I appreciate most about Kathy is her quest to make us all remember that we are teaching people and not just lecturing about Java. Her passion and desire for the highest quality education that meets the needs of the individual student is positively unparalleled at SunEd. Undoubtedly there are hundreds of students who have benefited from taking Kathy's classes."--Victor Peters, founder Next Step Education & Software Sun Certified Java Instructor"I want to thank Kathy for the EXCELLENT Study Guide. The book is well written, every concept is clearly explained using a real life example, and the book states what you specifically need to know for the exam. The way it's written, you feel that you're in a classroom and someone is actually teaching you the difficult concepts, but not in a dry, formal manner. The questions at the end of the chapters are also REALLY good, and I am sure they will help candidates pass the test. Watch out for this Wickedly Smart book."-Alfred Raouf, Web Solution Developer, Kemety.Net"The Sun Certification exam was certainly no walk in the park but Kathy's material allowed me to not only pass the exam, but Ace it "--Mary Whetsel, Sr. Technology Specialist, Application Strategy and Integration, The St. Paul Companies

    Like its sister textbook, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is enhanced by a cast of characters to help the reader on their way, hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.