With extensive treatment of the heart of epidemiology-from study designs to descriptive epidemiology to quantitative measures-this reader-friendly text is accessible and interesting to a wide range of beginning students in all health-related disciplines. A unique focus is given to real-world applications of epidemiology and the development of skills that students can apply in subsequent course work and in the field. The text is also accompanied by a complete package of instructor and student resources available through a companion Web site.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    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

    But where do they come from? What kind of environment breeds them? What sparks the flash of brilliance? How do we generate the breakthrough technologies that push forward our lives, our society, our culture? Steven Johnson's answers are revelatory as he identifies the seven key patterns behind genuine innovation, and traces them across time and disciplines. From Darwin and Freud to the halls of Google and Apple, Johnson investigates the innovation hubs throughout modern time and pulls out the approaches and commonalities that seem to appear at moments of originality.

    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.

    Within the industry, studies on game mechanics and behavioral psychology have become proliferate. However, few people understand how to merge the two fields into experience designs that reliably increases business metrics and generates a return on investment. Gamification Pioneer Yu-kai Chou takes reader on a journey to learn his twelve years of obsessive research in creating the Octalysis Framework, and how to apply the framework to create engaging and successful experiences in their product, workplace, marketing, and personal lives. Effective gamification is a combination of game design, game dynamics, behavioral economics, motivational psychology, UX/UI (User Experience and User Interface), neurobiology, technology platforms, as well as ROI-driving business implementations. This book explores the interplay between these disciplines to capture the core principles that contribute to good gamification design. The goal for this book is to become a strategy guide to help readers master the games that truly make a difference in their lives. Readers who absorb the contents of this book will have literally obtained what many companies pay tens of thousands of dollars to acquire. The ultimate aim is to enable the widespread adoption of good gamification and human-focused design in all types of industries.

    It was also a weapon.Simplicity isn’t just a design principle at Apple—it’s a value that permeates every level of the organization. The obsession with Simplicity is what separates Apple from other technology companies. It’s what helped Apple recover from near death in 1997 to become the most valuable company on Earth in 2011.Thanks to Steve Jobs’s uncompromising ways, you can see Simplicity in everything Apple does: the way it’s structured, the way it innovates, and the way it speaks to its customers.It’s by crushing the forces of Complexity that the company remains on its stellar trajectory.As ad agency creative director, Ken Segall played a key role in Apple’s resurrection, helping to create such critical marketing campaigns as Think different. By naming the iMac, he also laid the foundation for naming waves of i-products to come.Segall has a unique perspective, given his years of experience creating campaigns for other iconic tech companies, including IBM, Intel, and Dell. It was the stark contrast of Apple’s ways that made Segall appreciate the power of Simplicity—and inspired him to help others benefit from it.In Insanely Simple, you’ll be a fly on the wall inside a conference room with Steve Jobs, and on the receiving end of his midnight phone calls. You’ll understand how his obsession with Simplicity helped Apple perform better and faster, sometimes saving millions in the process. You’ll also learn, for example, how to:• Think Minimal: Distilling choices to a minimum brings clarity to a company and its customers—as Jobs proved when he replaced over twenty product models with a lineup of four.• Think Small: Swearing allegiance to the concept of “small groups of smart people” raises both morale and productivity.• Think Motion: Keeping project teams in constant motion focuses creative thinking on well-defined goals and minimizes distractions.• Think Iconic: Using a simple, powerful image to symbolize the benefit of a product or idea creates a deeper impression in the minds of customers.• Think War: Giving yourself an unfair advantage—using every weapon at your disposal—is the best way to ensure that your ideas survive unscathed.Segall brings Apple’s quest for Simplicity to life using fascinating (and previously untold) stories from behind the scenes. Through his insight and wit, you’ll discover how companies that leverage this power can stand out from competitors—and individuals who master it can become critical assets to their organizations.

    If you’re a musician or a hobbyist with experience in building electronic projects from kits or schematics, this do-it-yourself guide will walk you through the parts and schematics you need, and how to tailor them for your needs. Author Ray Wilson shares his decades of experience in synth-DIY, including the popular Music From Outer Space (MFOS) website and analog synth community.At the end of the book, you’ll apply everything you’ve learned by building an analog synthesizer, using the MFOS Noise Toaster kit. You’ll also learn what it takes to create synth-DIY electronic music studio. Get started in the fun and engaging hobby of synth-DIY without delay.With this book, you’ll learn:The differences between analog and digital synthesizersAnalog synthesizer building blocks, including VCOs, VCFs, VCAs, and LFOsHow to tool up for synth-DIY, including electronic instruments and suggestions for home-made equipmentFoundational circuits for amplification, biasing, and signal mixingHow to work with the MFOS Noise Toaster kitSetting up a synth-DIY electronic music studio on a budget

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

    It already drives most of the world’s top technology companies. And now it’s starting to spread to every domain where leaders wrestle with complex projects. If you’ve ever been startled by how fast the world is changing, Scrum is one of the reasons why. Productivity gains of as much as 1200% have been recorded, and there’s no more lucid – or compelling – explainer of Scrum and its bright promise than Jeff Sutherland, the man who put together the first Scrum team more than twenty years ago. The thorny problem Jeff began tackling back then boils down to this: people are spectacularly bad at doing things with agility and efficiency. Best laid plans go up in smoke. Teams often work at cross purposes to each other. And when the pressure rises, unhappiness soars. Drawing on his experience as a West Point-educated fighter pilot, biometrics expert, early innovator of ATM technology, and V.P. of engineering or CTO at eleven different technology companies, Jeff began challenging those dysfunctional realities, looking for solutions that would have global impact. In this book you’ll journey to Scrum’s front lines where Jeff’s system of deep accountability, team interaction, and constant iterative improvement is, among other feats, bringing the FBI into the 21st century, perfecting the design of an affordable 140 mile per hour/100 mile per gallon car, helping NPR report fast-moving action in the Middle East, changing the way pharmacists interact with patients, reducing poverty in the Third World, and even helping people plan their weddings and accomplish weekend chores. Woven with insights from martial arts, judicial decision making, advanced aerial combat, robotics, and many other disciplines, Scrum is consistently riveting. But the most important reason to read this book is that it may just help you achieve what others consider unachievable – whether it be inventing a trailblazing technology, devising a new system of education, pioneering a way to feed the hungry, or, closer to home, a building a foundation for your family to thrive and prosper.

    This internationally recognized standard provides the essential tools to practice project management and deliver organizational results.

    Creative Selection recounts the life of one of the few who worked behind the scenes, a highly-respected software engineer who worked in the final years the Steve Jobs era--the Golden Age of Apple.Ken Kocienda offers an inside look at Apple's creative process. For fifteen years, he was on the ground floor of the company as a specialist, directly responsible for experimenting with novel user interface concepts and writing powerful, easy-to-use software for products including the iPhone, the iPad, and the Safari web browser. His stories explain the symbiotic relationship between software and product development for those who have never dreamed of programming a computer, and reveal what it was like to work on the cutting edge of technology at one of the world's most admired companies.Kocienda shares moments of struggle and success, crisis and collaboration, illuminating each with lessons learned over his Apple career. He introduces the essential elements of innovation--inspiration, collaboration, craft, diligence, decisiveness, taste, and empathy--and uses these as a lens through which to understand productive work culture.An insider's tale of creativity and innovation at Apple, Creative Selection shows readers how a small group of people developed an evolutionary design model, and how they used this methodology to make groundbreaking and intuitive software which countless millions use every day.

    For anyone who has ever wondered how computers solve problems, an engagingly written guide for nonexperts to the basics of computer algorithms.

    Mountains of print have been written about culture. Loonshots identifies the small shifts in structure that control this transition, the same way that temperature controls the change from water to ice.Using examples that range from the spread of fires in forests to the hunt for terrorists online, and stories of thieves and geniuses and kings, Bahcall shows how this new kind of science helps us understand the behavior of companies and the fate of empires. Loonshots distills these insights into lessons for creatives, entrepreneurs, and visionaries everywhere.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.