Verification that algorithms work is emphasized more than their complexity. An effective use of examples, and huge number of interesting exercises, demonstrate the topics of trees and distance, matchings and factors, connectivity and paths, graph coloring, edges and cycles, and planar graphs. For those who need to learn to make coherent arguments in the fields of mathematics and computer science.

    Practical Algebra is an easy andfun-to-use workout program that quickly puts you in command of allthe basic concepts and tools of algebra. With the aid of practical, real-life examples and applications, you'll learn: * The basic approach and application of algebra to problemsolving * The number system (in a much broader way than you have known itfrom arithmetic) * Monomials and polynomials; factoring algebraic expressions; howto handle algebraic fractions; exponents, roots, and radicals;linear and fractional equations * Functions and graphs; quadratic equations; inequalities; ratio, proportion, and variation; how to solve word problems, andmore Authors Peter Selby and Steve Slavin emphasize practical algebrathroughout by providing you with techniques for solving problems ina wide range of disciplines--from engineering, biology, chemistry, and the physical sciences, to psychology and even sociology andbusiness administration. Step by step, Practical Algebra shows youhow to solve algebraic problems in each of these areas, then allowsyou to tackle similar problems on your own, at your own pace.Self-tests are provided at the end of each chapter so you canmeasure your mastery.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Covering all of the fundamentals in a straightforward, student-friendly manner, it is ideal for undergraduate- and graduate-level courses across the social sciences and also serves as an indispensable guide for researchers. Striking a balance between specific techniques and the underlying logic of scientific inquiry, this book provides a lucid treatment of the four major approaches to research: experimentation, survey research, field research, and the use of available data. Richly developed examples of empirical research and an emphasis on the research process enable students to better understand the real-world application of research methods. The authors also offer a unique chapter (13) advocating a multiple-methods strategy.

    He kept a day-by-day journal of his overland journey. Abbey provides a wealth of information about what it was like to travel overland by wagon in 1850.

    Only one man knew everything about Ronnie and Reggie Kray and that was their brother Charlie. Until now nobody has ever revealed the truth about the Firm.- Gossip and rumor have been rife, fact has blended into fiction and the unwritten law of the street meant that the real story was buried. But before his death, the eldest Kray brother, Charlie, decided to set the record straight once and for all. Revealing everything to Colin Fry, his co-author, he finally told his incredible story. By the man who knew them best, this is the ultimate history of the twins who ruled the East End with their peculiar blend of seductive glamour and terrifying violence.

    Part comedy of manners, part social commentary, love story, mystic narration and thriller, it is a sort of Indian version of Oliver Goldsmith's THE VICAR OF WAKEFIELD.

    Rather than relying on abstract generalizations and theories, van Manen offers an alternative that taps the unique nature of each human situation.The book offers detailed methodological explications and practical examples of hermeneutic-phenomenological inquiry. It shows how to orient oneself to human experience in education and how to construct a textual question which evokes a fundamental sense of wonder, and it provides a broad and systematic set of approaches for gaining experiential material that forms the basis for textual reflections.Van Manen also discusses the part played by language in educational research, and the importance of pursuing human science research critically as a semiotic writing practice. He focuses on the methodological function of anecdotal narrative in human science research, and offers methods for structuring the research text in relation to the particular kinds of questions being studied. Finally, van Manen argues that the choice of research method is itself a pedagogic commitment and that it shows how one stands in life as an educator.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    With his other 'shorter' collections Black + Blues and Third World Poems, Middle Passages creates a kind of chisel which may well lead us into a projected third trilogy. Here is a political angle to Brathwaite's Caribbean & New World quest, with new notes of protest and lament. It marks a Sisyphean stage of Third World history in which things fall apart and everyone's achievements come tumbling back down upon their heads and into their hearts, like the great stone which King Sisyphus was condemned to keep heaving back up the same hill in hell - a postmodernist implosion already signalled by Baldwin, Patterson, Soyinka and Achebe and more negatively by V.S. Naipaul; but given a new dimension here by Brathwaite's rhythmical and 'video' affirmations. And so Middle Passages includes poems for those modern heroes who are the pegs by which the mountain must be climbed again: Maroon resistance, the poets Nicolas Guillen, the Cuban revolutionary, and Mikey Smith, stoned to death on Stony Hill; the great musicians (Ellington, Bessie Smith); and Third World leaders Kwame Nkrumah, Walter Rodney and Nelson Mandela.

    In this book, a wealth of exercises are provided throughout each section, designed to reinforce learning and the logical comprehension of topics. The use of real data is incorporated much more extensively than in any other book on the market. Consist of strong coverage of computer-based methods, especially in the coverage of analysis of variance and regression. This text stresses mastery of methods most often used in medical research, with specific reference to actual medical literature and actual medical research. The approach minimizes mathematical formulation, yet gives complete explanations of all important concepts. Every new concept is systematically developed through completely worked-out examples from current medical research problems. Computer output is used to illustrate concepts when appropriate.

    Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.

    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.

    A History of Ireland explores the story of Ireland from the 12th century to the end of the 20th century. Written chronologically, it explores the period of the English invasion of Ireland, the emergence of a Gaelic culture, the religious conflicts across the centuries, the struggle over Home Rule, and the complex nature of the modern troubles. Covering the main political narratives of the country, A History of Ireland also delves into major economic, social, and cultural events, and offers a fascinating glimpse into Ireland’s past.

    It occurred, inevitably and temporarily, in the form of a capitalist economy and society, and it was also, perhaps, inevitable that it should occur in the form of a single "liberal" world economy, depending for a time on a single leading pioneer country. That country was Britain , and as such it stands alone in history. In his book E. J. Hobsbawm described and accounts for Britain's rise as the world's first industrial power, its decline from its temporary dominance, its rather special relationship with the rest of the world, and some of the effects of all of these on the life of the people of the country.The advantages of making an industrial revolution in the eighteenth and nineteenth centuries were considerable, but between the 1860s and the end of the nineteenth the disadvantages began to emerge. Britain's decline can be traced to the early and long-sustained start as an industrial power, which, among other things, embedded an archaic technology and business structure which became difficult to abandon, or even modify. Also, Britain became the primary agency of economic interchange between the advanced and backward nations, and this dependence of the underdeveloped world on Britain left her with a line of retreat into Empire and Free Trade. Between the wars, the single liberal world economy, theoretically self-regulating, collapsed, and the accompanying world political system also began to collapse after the Russian revolution of 1917. Britain has adjusted to these major changes, but the big question still remains--can Britain fully adapt to the changed economic world of the second half of the twentieth century and maintain a position as a major economy? And if not, what are the alternatives?Industry and Empire is the provocative and stimulating companion volume to Christopher Hill's Reformation to Industrial Revolution.