Now in a new Ninth Edition, this reader-friendly book has been completely revised and improved to ensure that the learning experience is enhanced. It's built on the strength of Irwin's problem-solving methodology, providing readers with a strong foundation as they advance in the field.

    In writing the book James Stewart asked himself: What is essential for a three-semester calculus course for scientists and engineers? Stewart's ESSENTIAL CALCULUS offers a concise approach to teaching calculus that focuses on major concepts and supports those concepts with precise definitions, patient explanations, and carefully graded problems. Essential Calculus is only 850 pages-two-thirds the size of Stewart's other calculus texts (CALCULUS, Fifth Edition and CALCULUS, EARLY TRANSCENDENTALS, Fifth Edition)-and yet it contains almost all of the same topics. The author achieved this relative brevity mainly by condensing the exposition and by putting some of the features on the website, www.StewartCalculus.com. Despite the reduced size of the book, there is still a modern flavor: Conceptual understanding and technology are not neglected, though they are not as prominent as in Stewart's other books. ESSENTIAL CALCULUS has been written with the same attention to detail, eye for innovation, and meticulous accuracy that have made Stewart's textbooks the best-selling calculus texts in the world.

    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.

    Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

    Try out more than 1,000 commands to find and get software, monitor system health and security, and access network resources. Then, apply the skills you learn from this book to use and administer desktops and servers running Ubuntu, Debian, and KNOPPIX or any other Linux distribution.

    This book is an easy-to-understand and fun reference to this challenging subject. It explains the principles of organic chemistry in simple terms and includes worked-out problems to help readers get up to speed on the basics.

    It takes a fairly traditional approach, emphasizing problem solving, design, and programming as the core skills of computer science. However, these ideas are illustrated using a non-traditional language, namely Python. Although I use Python as the language, teaching Python is not the main point of this book. Rather, Python is used to illustrate fundamental principles of design and programming that apply in any language or computing environment. In some places, I have purposely avoided certain Python features and idioms that are not generally found in other languages. There are already many good books about Python on the market; this book is intended as an introduction to computing. Features include the following: *Extensive use of computer graphics. *Interesting examples. *Readable prose. *Flexible spiral coverage. *Just-in-time object coverage. *Extensive end-of-chapter problems.

    It covers all fundamental subjects, including elasticity, structural analysis, airworthiness and aeroelasticity. Now in its fourth edition, the author has revised and updated the text throughout and added new case study and worked example material to make the text even more accessible.The leading Aircraft Structures text, covering a complete course from basic structural mechanics to finite element analysisEnhanced pedagogy with additional case studies, worked examples and home work exercises

    Providing a concise introduction to abstract algebra, this work unfolds some of the fundamental systems with the aim of reaching applicable, significant results.

    Lehninger Principles of Biochemistry, Fourth Edition brings clarity and coherence to an often unwieldy discipline, while incorporating the field's most important recent developments and applications.

    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.

    Oriented toward traditional black and white photography, the book also explores digital techniques and web photography resources, equipment, the exposure and development of film, and the making and finishing of prints.

    

    Its unique approach communicates the richness and diversity of CIS in a lucid and accessible format. This fully revised and updated second edition reinforces the view of CIS as a gateway to science and problem solving, sets out the scientific principles that govern its use, and describes the impact of people on its development, design, and success. The second edition of Geographic Information Systems and Science includes:A new five-part structure: Foundations; Principles; Techniques; Analysis; and Management and Policy.All-new personality boxes of current GIS practitioners.New real-world applications of GIS.New or expanded coverage of important current topics:Location-based servicesDistributed computingVirtual and augmented realitiesHomeland securityBusiness GIS and geodemographicsThe emergence of geoportalsGrand challenges of GIScienceA new suite of instructor and student resources http://www.wiley.com/go/longleyThe second edition of Geographic Information Systems and Science is essential reading for undergraduates taking courses in GIS within departments of Geography, Environmental Science, Business (and Public) Administration, Computer Science, Urban Studies, Planning, Information Science, Civil Engineering, and Archaeology. It is also provides a key resource for foundation GIS courses on taught MSc and other higher-degree programs. Professional users of GIS from governmental organizations and industries across the private sector will find this book an invaluable resource with a wealth of relevant applications.

    Generous support from a number of foundations provided the means for assembling and maintaining an experienced staff to co-operate with members of the Institute's Physics Department in the examination, improvement, and development of physics curriculum materials for students planning careers in the sciences. After careful analysis of objectives and the problems involved, preliminary versions of textbooks were prepared, tested through classroom use at M.I.T. and other institutions, re-evaluated, rewritten, and tried again. Only then were the final manuscripts undertaken.