Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud-computing technologies. This collection of essays expands on the vision of pioneering computer scientist Jim Gray for a new, fourth paradigm of discovery based on data-intensive science and offers insights into how it can be fully realized.

    It's about states, armies and corporations. It's about orders from on high. Even history "from below" is often about trade unions and workers' parties. But what if that's simply because hierarchical institutions create the archives that historians rely on? What if we are missing the informal, less well documented social networks that are the true sources of power and drivers of change?The 21st century has been hailed as the Age of Networks. However, in The Square and the Tower, Niall Ferguson argues that networks have always been with us, from the structure of the brain to the food chain, from the family tree to freemasonry. Throughout history, hierarchies housed in high towers have claimed to rule, but often real power has resided in the networks in the town square below. For it is networks that tend to innovate. And it is through networks that revolutionary ideas can contagiously spread. Just because conspiracy theorists like to fantasize about such networks doesn't mean they are not real.From the cults of ancient Rome to the dynasties of the Renaissance, from the founding fathers to Facebook, The Square and the Tower tells the story of the rise, fall and rise of networks, and shows how network theory--concepts such as clustering, degrees of separation, weak ties, contagions and phase transitions--can transform our understanding of both the past and the present.Just as The Ascent of Money put Wall Street into historical perspective, so The Square and the Tower does the same for Silicon Valley. And it offers a bold prediction about which hierarchies will withstand this latest wave of network disruption--and which will be toppled.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    With a blend of software engineering facts and thought-provoking opinions, Fred Brooks offers insight for anyone managing complex projects. These essays draw from his experience as project manager for the IBM System/360 computer family and then for OS/360, its massive software system. Now, 45 years after the initial publication of his book, Brooks has revisited his original ideas and added new thoughts and advice, both for readers already familiar with his work and for readers discovering it for the first time.The added chapters contain (1) a crisp condensation of all the propositions asserted in the original book, including Brooks' central argument in The Mythical Man-Month: that large programming projects suffer management problems different from small ones due to the division of labor; that the conceptual integrity of the product is therefore critical; and that it is difficult but possible to achieve this unity; (2) Brooks' view of these propositions a generation later; (3) a reprint of his classic 1986 paper "No Silver Bullet"; and (4) today's thoughts on the 1986 assertion, "There will be no silver bullet within ten years."

    C. R. Licklider, whose visionary dream of a human-computer symbiosis transformed the course of modern science and led to the development of the personal computer. Reprint.

    How have we achieved so much despite understanding so little? Cognitive scientists Steven Sloman and Philip Fernbach argue that we survive and thrive despite our mental shortcomings because we live in a rich community of knowledge. The key to our intelligence lies in the people and things around us. We're constantly drawing on information and expertise stored outside our heads: in our bodies, our environment, our possessions, and the community with which we interact--and usually we don't even realize we're doing it. The human mind is both brilliant and pathetic. We have mastered fire, created democratic institutions, stood on the moon, and sequenced our genome. And yet each of us is error prone, sometimes irrational, and often ignorant. The fundamentally communal nature of intelligence and knowledge explains why we often assume we know more than we really do, why political opinions and false beliefs are so hard to change, and why individually oriented approaches to education and management frequently fail. But our collaborative minds also enable us to do amazing things. This book contends that true genius can be found in the ways we create intelligence using the world around us.

    Incorporating the latest advances in brain scanning and neuroscience, Dutton demonstrates that the brilliant neurosurgeon who lacks empathy has more in common with a Ted Bundy who kills for pleasure than we may wish to admit, and that a mugger in a dimly lit parking lot may well, in fact, have the same nerveless poise as a titan of industry.Dutton argues that there are indeed “functional psychopaths” among us—different from their murderous counterparts—who use their detached, unflinching, and charismatic personalities to succeed in mainstream society, and that shockingly, in some fields, the more “psychopathic” people are, the more likely they are to succeed. Dutton deconstructs this often misunderstood diagnosis through bold on-the-ground reporting and original scientific research as he mingles with the criminally insane in a high-security ward, shares a drink with one of the world’s most successful con artists, and undergoes transcranial magnetic stimulation to discover firsthand exactly how it feels to see through the eyes of a psychopath.As Dutton develops his theory that we all possess psychopathic tendencies, he puts forward the argument that society as a whole is more psychopathic than ever: after all, psychopaths tend to be fearless, confident, charming, ruthless, and focused—qualities that are tailor-made for success in the twenty-first century. Provocative at every turn, The Wisdom of Psychopaths is a riveting adventure that reveals that it’s our much-maligned dark side that often conceals the trump cards of success.

    He had mentored many tech leaders in his illustrious career as an investor, but few things had made him prouder, or been better for his fund's bottom line, than his early service to Mark Zuckerberg. Still a large shareholder in Facebook, he had every good reason to stay on the bright side. Until he simply couldn't. ZUCKED is McNamee's intimate reckoning with the catastrophic failure of the head of one of the world's most powerful companies to face up to the damage he is doing. It's a story that begins with a series of rude awakenings. First there is the author's dawning realization that the platform is being manipulated by some very bad actors. Then there is the even more unsettling realization that Zuckerberg and Sheryl Sandberg are unable or unwilling to share his concerns, polite as they may be to his face."

    . . a lively, engaging masterpiece."--Erik Brynjolfsson, bestselling co-author of The Second Machine AgeMIT professor Sinan Aral isn't only one of the world's leading experts on social media--he's also an entrepreneur and investor, giving him an unparalleled 360-degree view of the technology's great promise as well as its outsize capacity to damage our politics, our economy, and even our personal health.Drawing on two decades of his own research and business experience, Aral goes under the hood of the biggest, most powerful social networks to tackle the critical question of just how much social media actually shapes our choices, for better or worse. Aral shows how the tech behind social media offers the same set of behavior-influencing levers to both Russian hackers and brand marketers--to everyone who hopes to change the way we think and act--which is why its consequences affect everything from elections to business, dating to health. Along the way, he covers a wide array of topics, including how network effects fuel Twitter's and Facebook's massive growth to the neuroscience of how social media affects our brains, the real consequences of fake news, the power of social ratings, and the impact of social media on our kids.In mapping out strategies for being more thoughtful consumers of social media, The Hype Machine offers the definitive guide to understanding and harnessing for good the technology that has redefined our world overnight.

    Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.

    In Zero to One, legendary entrepreneur and investor Peter Thiel shows how we can find singular ways to create those new things. Thiel begins with the contrarian premise that we live in an age of technological stagnation, even if we’re too distracted by shiny mobile devices to notice. Information technology has improved rapidly, but there is no reason why progress should be limited to computers or Silicon Valley. Progress can be achieved in any industry or area of business. It comes from the most important skill that every leader must master: learning to think for yourself.Doing what someone else already knows how to do takes the world from 1 to n, adding more of something familiar. But when you do something new, you go from 0 to 1. The next Bill Gates will not build an operating system. The next Larry Page or Sergey Brin won’t make a search engine. Tomorrow’s champions will not win by competing ruthlessly in today’s marketplace. They will escape competition altogether, because their businesses will be unique. Zero to One presents at once an optimistic view of the future of progress in America and a new way of thinking about innovation: it starts by learning to ask the questions that lead you to find value in unexpected places.

    But throughout the 1960s and 1970s a diverse group of teachers and students working together on academic computing systems conducted many of the activities we now recognize as personal and social computing. Their networks were centered in New Hampshire, Minnesota, and Illinois, but they connected far-flung users. Joy Rankin draws on detailed records to explore how users exchanged messages, programmed music and poems, fostered communities, and developed computer games like The Oregon Trail. These unsung pioneers helped shape our digital world, just as much as the inventors, garage hobbyists, and eccentric billionaires of Palo Alto.By imagining computing as an interactive commons, the early denizens of the digital realm seeded today's debate about whether the internet should be a public utility and laid the groundwork for the concept of net neutrality. Rankin offers a radical precedent for a more democratic digital culture, and new models for the next generation of activists, educators, coders, and makers.

    The Truth Machine is the best book so far on what has happened and what may come along. It demands the attention of anyone concerned with our economic future." --Lawrence H. Summers, Charles W. Eliot University Professor and President Emeritus at Harvard, Former Treasury SecretaryFrom Michael J. Casey and Paul Vigna, the authors of The Age of Cryptocurrency, comes the definitive work on the Internet's Next Big Thing: The Blockchain.Big banks have grown bigger and more entrenched. Privacy exists only until the next hack. Credit card fraud is a fact of life. Many of the "legacy systems" once designed to make our lives easier and our economy more efficient are no longer up to the task. Yet there is a way past all this--a new kind of operating system with the potential to revolutionize vast swaths of our economy: the blockchain.In The Truth Machine, Michael J. Casey and Paul Vigna demystify the blockchain and explain why it can restore personal control over our data, assets, and identities; grant billions of excluded people access to the global economy; and shift the balance of power to revive society's faith in itself. They reveal the disruption it promises for industries including finance, tech, legal, and shipping.Casey and Vigna expose the challenge of replacing trusted (and not-so-trusted) institutions on which we've relied for centuries with a radical model that bypasses them. The Truth Machine reveals the empowerment possible when self-interested middlemen give way to the transparency of the blockchain, while highlighting the job losses, assertion of special interests, and threat to social cohesion that will accompany this shift. With the same balanced perspective they brought to The Age of Cryptocurrency, Casey and Vigna show why we all must care about the path that blockchain technology takes--moving humanity forward, not backward.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results