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.

    With a new introduction, three new chapters, modernized language and methods throughout, and an appendix of challenging and enjoyable practice problems, Calculus Made Easy has been thoroughly updated for the modern reader.

    It starts in your mother's womb, accelerates to high speed in infancy and childhood, and continues through every age, whether you're actively engaged in mastering a new skill, intuitively discovering an unfamiliar place, or just sleeping, which is fundamental to helping you consolidate and hold on to what you've learned. You are truly born to learn around the clock.But few of us know how we learn, which is the key to learning and studying more effectively. For example, you may be surprised by the following:People tend to misjudge what they have learned well, what they don't yet know, and what they do and do not need to practice.Moments of confusion, frustration, uncertainty, and lack of confidence are part of the process of acquiring new skills and new knowledge.Humans and animals explore their worlds for the sake of learning, regardless of rewards and punishment connected with success.You can teach an old dog new tricks. In fact, older learners have the benefit of prior knowledge and critical skills—two advantages in learning.Shedding light on what's going on when we learn and dispelling common myths about the subject, How We Learn introduces you to this practical and accessible science in 24 half-hour lectures presented by Professor Monisha Pasupathi of the University of Utah, an award-winning psychology teacher and expert on how people of all ages learn.

    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.

    Features 16 tear-out model planes.     The New World Champion Paper Airplane Book chronicles the creation of the new distance champion paper airplane and how it broke the world record. Collins's revolutionary approach to plane design is a departure from all previous record holders and represents the most important development in paper airplane design in decades. This entertaining guide also contains 19 other amazing designs with step-by-step instructional photos, including a novel locking technique, a pioneering cambered-wing plane, and multiple long-flying aircraft that soar for minutes rather than seconds. A 32-page insert of full-color tear-out paper airplane models are printed on regulation-weight, durable paper stock for hours of flying fun.

    

    But it can be even trickier to use than either Unix or Linux, and harder still to master.Absolute FreeBSD, 2nd Edition is your complete guide to FreeBSD, written by FreeBSD committer Michael W. Lucas. Lucas considers this completely revised and rewritten second edition of his landmark work to be his best work ever; a true product of his love for FreeBSD and the support of the FreeBSD community. Absolute FreeBSD, 2nd Edition covers installation, networking, security, network services, system performance, kernel tweaking, filesystems, SMP, upgrading, crash debugging, and much more, including coverage of how to:Use advanced security features like packet filtering, virtual machines, and host-based intrusion detection Build custom live FreeBSD CDs and bootable flash Manage network services and filesystems Use DNS and set up email, IMAP, web, and FTP services for both servers and clients Monitor your system with performance-testing and troubleshooting tools Run diskless systems Manage schedulers, remap shared libraries, and optimize your system for your hardware and your workload Build custom network appliances with embedded FreeBSD Implement redundant disks, even without special hardware Integrate FreeBSD-specific SNMP into your network management system. Whether you're just getting started with FreeBSD or you've been using it for years, you'll find this book to be the definitive guide to FreeBSD that you've been waiting for.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    Less than 20 years after its founding, it boasts the largest constellation of commercial satellites in orbit, has pioneered reusable rockets, and in 2020 became the first private company to launch human beings into orbit. Half a century after the space race it is private companies, led by SpaceX, standing alongside NASA pushing forward into the cosmos, and laying the foundation for our exploration of other worlds.But before it became one of the most powerful players in the aerospace industry, SpaceX was a fledgling startup, scrambling to develop a single workable rocket before the money ran dry. The engineering challenge was immense; numerous other private companies had failed similar attempts. And even if SpaceX succeeded, they would then have to compete for government contracts with titans such as Lockheed Martin and Boeing, who had tens of thousands of employees and tens of billions of dollars in annual revenue. SpaceX had fewer than 200 employees and the relative pittance of $100 million in the bank.In Liftoff, Eric Berger, senior space editor at Ars Technica, takes readers inside the wild early days that made SpaceX. Focusing on the company’s first four launches of the Falcon 1 rocket, he charts the bumpy journey from scrappy underdog to aerospace pioneer. We travel from company headquarters in El Segundo, to the isolated Texas ranchland where they performed engine tests, to Kwajalein, the tiny atoll in the Pacific where SpaceX launched the Falcon 1. Berger has reported on SpaceX for more than a decade, enjoying unparalleled journalistic access to the company’s inner workings. Liftoff is the culmination of these efforts, drawing upon exclusive interviews with dozens of former and current engineers, designers, mechanics, and executives, including Elon Musk. The enigmatic Musk, who founded the company with the dream of one day settling Mars, is the fuel that propels the book, with his daring vision for the future of space.Filled with never-before-told stories of SpaceX’s turbulent beginning, Liftoff is a saga of cosmic proportions.

    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

    The proliferation of fast-moving technologies, including forms of artificial intelligence, will cause us to confront profound questions about ourselves. The era of human intellectual superiority is ending, and, as a species, we need to plan for this monumental shift.A Human Algorithm: How Artificial Intelligence Is Redefining Who We Are examines the immense impact intelligent technology will have on humanity. These machines, while challenging our personal beliefs and our socio-economic world order, also have the potential to transform our health and well-being, alleviate poverty and suffering, and reveal the mysteries of intelligence and consciousness. International human rights attorney Flynn Coleman deftly argues that it is critical we instill values, ethics, and morals into our robots, algorithms, and other forms of AI. Equally important, we need to develop and implement laws, policies, and oversight mechanisms to protect us from tech’s insidious threats.To realize AI’s transcendent potential, Coleman advocates for inviting a diverse group of voices to participate in designing our intelligent machines and using our moral imagination to ensure that human rights, empathy, and equity are core principles of emerging technologies. Ultimately, A Human Algorithm is a clarion call for building a more humane future and moving conscientiously into a new frontier of our own design.

    A leader in the emerging field of longevity offers his perspective on what cutting-edge breakthroughs are on the horizon, as well as the practical steps we can take now to live healthily to 100 and beyond.In The Science and Technology of Growing Young, industry investor and insider Sergey Young demystifies the longevity landscape, cutting through the hype and showing readers what they can do now to live better for longer, and offering a look into the exciting possibilities that await us. By viewing aging as a condition that can be cured, we can dramatically revolutionize the field of longevity and make it accessible for everyone.Join Sergey as he gathers insights from world-leading health entrepreneurs, scientists, doctors, and inventors, providing a comprehensive look into the future of longevity in two horizons:The Near Horizon of Longevity identifies the technological developments that will allow us to live to 150--some of which are already in use--from AI-based diagnostics to gene editing and organ regeneration.The Far Horizon of Longevity offers a tour of the future of age reversal, and the exciting technologies that will allow us to live healthily to 200, from Internet of Bodies to digital avatars to AI-brain integration. In a bonus chapter, Sergey also showcases 10 longevity choices that we already know and can easily implement to live to 100, distilling the science behind diet, exercise, sleep, mental health, and our environments into attainable habits and lifestyle hacks that anyone can adopt to vastly improve their lives and workplaces.Combining practical advice with an incredible overview of the brave new world to come, The Science and Technology of Growing Young redefines what it means to be human and to grow young.

    Drawing on their extraordinary experience, they introduce a start-to-finish methodology for "ripping apart" applications to reveal even the most subtle and well-hidden security flaws.

    They are being told that buying organic foods, unprocessed and sourced from small local farms, is the most healthful and sustainable option. Now, Robert Paarlberg reviews the evidence and finds abundant reason to disagree. He delineates the ways in which global food markets have in fact improved our diet, and how industrial farming has recently turned green, thanks to GPS-guided precision methods that cut energy use and chemical pollution. He makes clear that America's serious obesity crisis does not come from farms, or from food deserts, but instead from food swamps created by food companies, retailers, and restaurant chains. And he explains how, though animal welfare is lagging behind, progress can be made through continued advocacy, more progressive regulations, and perhaps plant-based imitation meat. He finds solutions that can make sense for farmers and consumers alike and provides a road map through the rapidly changing worlds of food and farming, laying out a practical path to bring the two together.