Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge.Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data- including stream data, sequence data, graph structured data, social network data, and multi-relational data.A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business dataUpdates that incorporate input from readers, changes in the field, and more material on statistics and machine learningDozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projectsComplete classroom support for instructors at www.mkp.com/datamining2e companion site

    Whether you're building the next killer app, investing in a startup, or simply curious about the technology, this practical book is essential reading.Bitcoin, the first successful decentralized digital currency, is still in its infancy and it's already spawned a multi-billion dollar global economy. This economy is open to anyone with the knowledge and passion to participate. Mastering Bitcoin provides you with the knowledge you need (passion not included).This book includes:A broad introduction to bitcoin--ideal for non-technical users, investors, and business executivesAn explanation of the technical foundations of bitcoin and cryptographic currencies for developers, engineers, and software and systems architectsDetails of the bitcoin decentralized network, peer-to-peer architecture, transaction lifecycle, and security principlesOffshoots of the bitcoin and blockchain inventions, including alternative chains, currencies, and applicationsUser stories, analogies, examples, and code snippets illustrating key technical concepts

    Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University

    The book begins with the basic concepts of logic and set theory, to familiarize students with the language of mathematics and how it is interpreted. These concepts are used as the basis for a step-by-step breakdown of the most important techniques used in constructing proofs. To help students construct their own proofs, this new edition contains over 200 new exercises, selected solutions, and an introduction to Proof Designer software. No background beyond standard high school mathematics is assumed. Previous Edition Hb (1994) 0-521-44116-1 Previous Edition Pb (1994) 0-521-44663-5

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    It covers such areas as biotechnology and biomedical engineering.

    If you're a reasonably proficient programmer who can think logically, you have all the background you'll need. Stepanov and Rose introduce the relevant abstract algebra and number theory with exceptional clarity. They carefully explain the problems mathematicians first needed to solve, and then show how these mathematical solutions translate to generic programming and the creation of more effective and elegant code. To demonstrate the crucial role these mathematical principles play in many modern applications, the authors show how to use these results and generalized algorithms to implement a real-world public-key cryptosystem. As you read this book, you'll master the thought processes necessary for effective programming and learn how to generalize narrowly conceived algorithms to widen their usefulness without losing efficiency. You'll also gain deep insight into the value of mathematics to programming--insight that will prove invaluable no matter what programming languages and paradigms you use. You will learn aboutHow to generalize a four thousand-year-old algorithm, demonstrating indispensable lessons about clarity and efficiencyAncient paradoxes, beautiful theorems, and the productive tension between continuous and discreteA simple algorithm for finding greatest common divisor (GCD) and modern abstractions that build on itPowerful mathematical approaches to abstractionHow abstract algebra provides the idea at the heart of generic programmingAxioms, proofs, theories, and models: using mathematical techniques to organize knowledge about your algorithms and data structuresSurprising subtleties of simple programming tasks and what you can learn from themHow practical implementations can exploit theoretical knowledge

    Calculus is not a prerequisite, although examples and exercises using very basic calculus are included (labeled Calculus Required.) The most technology-friendly text on the market, Introductory Linear Algebra is also the most flexible. By omitting certain sections, instructors can cover the essentials of linear algebra (including eigenvalues and eigenvectors), to show how the computer is used, and to introduce applications of linear algebra in a one-semester course.

    The British expected R.101 to spearhead a fleet of imperial airships that would dominate the skies as British naval ships, a century earlier, had ruled the seas. The dream ended when, on its demonstration flight to India, R.101 crashed in France, tragically killing nearly all aboard.Combining meticulous research with superb storytelling, Fatal Flight guides us from the moment the great airship emerged from its giant shed—nearly the largest building in the British Empire—to soar on its first flight, to its last fateful voyage. The full story behind R.101 shows that, although it was a failure, it was nevertheless a supremely imaginative human creation. The technical achievement of creating R.101 reveals the beauty, majesty, and, of course, the sorrow of the human experience.The narrative follows First Officer Noel Atherstone and his crew from the ship’s first test flight in 1929 to its fiery crash on October 5, 1930. It reveals in graphic detail the heroic actions of Atherstone as he battled tremendous obstacles. He fought political pressures to hurry the ship into the air, fended off Britain’s most feted airship pilot, who used his influence to take command of the ship and nearly crashed it, and, a scant two months before departing for India, guided the rebuilding of the ship to correct its faulty design. After this tragic accident, Britain abandoned airships, but R.101 flew again, its scrap melted down and sold to the Zeppelin Company, who used it to create LZ 129, an airship even more mighty than R.101—and better known as the Hindenburg. Set against the backdrop of the British Empire at the height of its power in the early twentieth century,Fatal Flight portrays an extraordinary age in technology, fueled by humankind’s obsession with flight.

    It has become popular in recent years because of its simplicity, conciseness, and clarity. This book teaches functional programming as a way of thinking and problem solving, using Haskell, the most popular purely functional language. Rather than using the conventional (boring) mathematical examples commonly found in other programming language textbooks, the author uses examples drawn from multimedia applications, including graphics, animation, and computer music, thus rewarding the reader with working programs for inherently more interesting applications. Aimed at both beginning and advanced programmers, this tutorial begins with a gentle introduction to functional programming and moves rapidly on to more advanced topics. Details about progamming in Haskell are presented in boxes throughout the text so they can be easily found and referred to.

    Joining the professional web designers and programmers are new audiences who need to know a little bit of code at work (update a content management system or e-commerce store) and those who want to make their personal blogs more attractive. Many books teaching HTML and CSS are dry and only written for those who want to become programmers, which is why this book takes an entirely new approach. • Introduces HTML and CSS in a way that makes them accessible to everyone—hobbyists, students, and professionals—and it’s full-color throughout • Utilizes information graphics and lifestyle photography to explain the topics in a simple way that is engaging • Boasts a unique structure that allows you to progress through the chapters from beginning to end or just dip into topics of particular interest at your leisureThis educational book is one that you will enjoy picking up, reading, then referring back to. It will make you wish other technical topics were presented in such a simple, attractive and engaging way!

    The principal enhancement in Java 8 was the addition of functional programming constructs to Java's object-oriented roots. Java 7, 8, and 9 also introduced language features, such as the try-with-resources statement, the diamond operator for generic types, default and static methods in interfaces, the @SafeVarargs annotation, and modules. New library features include pervasive use of functional interfaces and streams, the java.time package for manipulating dates and times, and numerous minor enhancements such as convenience factory methods for collections. In this new edition of Effective Java, Bloch updates the work to take advantage of these new language and library features, and provides specific best practices for their use. Java's increased support for multiple paradigms increases the need for best-practices advice, and this book delivers. As in previous editions, each chapter consists of several "items," each presented in the form of a short, standalone essay that provides specific advice, insight into Java platform subtleties, and updated code examples. The comprehensive descriptions and explanations for each item illuminate what to do, what not to do, and why. Coverage includes:Updated techniques and best practices on classic topics, including objects, classes, methods, libraries, and generics How to avoid the traps and pitfalls of commonly misunderstood subtleties of the platform Focus on the language and its most fundamental libraries, such as java.lang and java.util

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    Topics covered include matrix multiplication, row reduction, matrix inverse, orthogonality and computation. The self-teaching book is loaded with examples and graphics and provides a wide array of probing problems, accompanying solutions, and a glossary. Chapter 1: Introduction to Vectors; Chapter 2: Solving Linear Equations; Chapter 3: Vector Spaces and Subspaces; Chapter 4: Orthogonality; Chapter 5: Determinants; Chapter 6: Eigenvalues and Eigenvectors; Chapter 7: Linear Transformations; Chapter 8: Applications; Chapter 9: Numerical Linear Algebra; Chapter 10: Complex Vectors and Matrices; Solutions to Selected Exercises; Final Exam. Matrix Factorizations. Conceptual Questions for Review. Glossary: A Dictionary for Linear Algebra Index Teaching Codes Linear Algebra in a Nutshell.

    The R language is recognised as one of the most powerful and flexible statistical software packages, and it enables the user to apply many statistical techniques that would be impossible without such software to help implement such large data sets.