The world is more complex and volatile today than at any other time in our history. The tools of our modern existence are getting faster, cheaper, and smaller at an exponential rate, transforming every aspect of society, from business to culture and from the public sphere to our most private moments. The people who succeed will be the ones who learn to think differently. In Whiplash, Joi Ito and Jeff Howe distill that logic into nine organizing principles for navigating and surviving this tumultuous period: Emergence over AuthorityPull over PushCompasses over MapsRisk over SafetyDisobedience over CompliancePractice over TheoryDiversity over AbilityResilience over StrengthSystems over Objects Filled with incredible case studies and cutting-edge research and philosophies from the MIT Media Lab and beyond, Whiplash will help you adapt and succeed in this unpredictable world.

    The concepts and techniques described are the actual ones used by real game studios like Electronic Arts and Naughty Dog. The examples are often grounded in specific technologies, but the discussion extends way beyond any particular engine or API. The references and citations make it a great jumping off point for those who wish to dig deeper into any particular aspect of the game development process.Intended as the text for a college level series in game programming, this book can also be used by amateur software engineers, hobbyists, self-taught game programmers, and existing members of the game industry. Junior game engineers can use it to solidify their understanding of game technology and engine architecture. Even senior engineers who specialize in one particular field of game development can benefit from the bigger picture presented in these pages.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    Another AI discovered a new antibiotic by analyzing molecular properties human scientists did not understand. Now, AI-powered jets are defeating experienced human pilots in simulated dogfights. AI is coming online in searching, streaming, medicine, education, and many other fields and, in so doing, transforming how humans are experiencing reality.In The Age of AI, three leading thinkers have come together to consider how AI will change our relationships with knowledge, politics, and the societies in which we live. The Age of AI is an essential roadmap to our present and our future, an era unlike any that has come before.

    In Dataclysm, Christian Rudder uses it to show us who we truly are.   For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers.   In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.   Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.

    This fast-moving narrative starts at ground zero, with the dramatic incubation of open-source software by Linux and its enigmatic creator, Linus Torvalds. With firsthand accounts, it describes how a motley group of programmers managed to shake up the computing universe and cause a radical shift in thinking for the post-Microsoft era. A powerful and engaging tale of innovation versus big business, Rebel Code chronicles the race to create and perfect open-source software, and provides the ideal perch from which to explore the changes that cyberculture has engendered in our society. Based on over fifty interviews with open-source protagonists such as Torvalds and open source guru Richard Stallman, Rebel Code captures the voice and the drama behind one of the most significant business trends in recent memory.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    Users demand software that is well-behaved, good-looking, and easy to use. Your clients or managers demand originality and a short time to market. Your UI technology -- web applications, desktop software, even mobile devices -- may give you the tools you need, but little guidance on how to use them well.UI designers over the years have refined the art of interface design, evolving many best practices and reusable ideas. If you learn these, and understand why the best user interfaces work so well, you too can design engaging and usable interfaces with less guesswork and more confidence.Designing Interfaces captures those best practices as design patterns -- solutions to common design problems, tailored to the situation at hand. Each pattern contains practical advice that you can put to use immediately, plus a variety of examples illustrated in full color. You'll get recommendations, design alternatives, and warnings on when not to use them.Each chapter's introduction describes key design concepts that are often misunderstood, such as affordances, visual hierarchy, navigational distance, and the use of color. These give you a deeper understanding of why the patterns work, and how to apply them with more insight.A book can't design an interface for you -- no foolproof design process is given here -- but Designing Interfaces does give you concrete ideas that you can mix and recombine as you see fit. Experienced designers can use it as a sourcebook of ideas. Novice designers will find a roadmap to the world of interface and interaction design, with enough guidance to start using these patterns immediately.

    This book aims to minimize the complexity of user-centered design for the Web with explanations and illustrations that focus on ideas rather than tools or techniques.

    The book offers clear instruction and real-world examples from training expert and bestselling author Mike Meyers along with hundreds of accurate practice questions.Fulfilling the promise of the All-in-One series, this complete reference serves both as a study tool and a valuable on-the-job reference that will serve readers beyond the exam. CompTIA Network+ Certification All-in-One Exam Guide, Seventh Edition (Exam N10-007) also includes access to free video training and interactive hands-on labs and simulations that prepare you for difficult performance-based questions. A valuable pre-assessment test enables readers to gauge their familiarity with the test’s objectives and tailor an effective course for study.-Contains complete coverage of every objective for the CompTIA Network+ Certification exam-Written by CompTIA training and certification guru Mike Meyers- Electronic content includes the Total Tester exam simulator with over 100 practice questions, over an hour of training videos, and a collection of Mike Meyers’ favorite shareware and freeware networking utilities

    This brilliant work heralds the new age of nanotechnology, which will give us thorough and inexpensive control of the structure of matter.  Drexler examines the enormous implications of these developments for medicine, the economy, and the environment, and makes astounding yet well-founded projections for the future.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    A whole new generation is turning to his work to understand a global village made real by the information superhighway and the overwhelming challenge of electronic transformation. “Before anyone could perceive the electric form of the information revolution, McLuhan was publishing brilliant explanations of the perceptual changes being experienced by the users of mass media. He seemed futuristic to some and an enemy of print and literacy to others. He was, in reality, a deeply literate man of astonishing prescience. Tom Wolfe suggested aloud that McLuhan’s work was as important culturally as that of Darwin or Freud. Agreement and scoffing ensued. Increasingly Wolfe’s wonder seems justified.” From the Introduction Here in one volume, are McLuhan’s key ideas, drawn from his books, articles, correspondence, and published speeches. This book is the essential archive of his constantly surprising vision.