Then he wrote a groundbreaking operating system and distributed it via the Internet -- for free. Today Torvalds is an international folk hero. And his creation LINUX is used by over 12 million people as well as by companies such as IBM.Now, in a narrative that zips along with the speed of e-mail, Torvalds gives a history of his renegade software while candidly revealing the quirky mind of a genius. The result is an engrossing portrayal of a man with a revolutionary vision, who challenges our values and may change our world.

    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.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    He believes that we should investigate what makes some countries more capable than others. Complex products—from films to robots, apps to automobiles—are a physical distillation of an economy’s knowledge, a measurable embodiment of its education, infrastructure, and capability. Economic wealth accrues when applications of this knowledge turn ideas into tangible products; the more complex its products, the more economic growth a country will experience.A radical new interpretation of global economics, Why Information Grows overturns traditional assumptions about the development of economies and the origins of wealth and takes a crucial step toward making economics less the dismal science and more the insightful one.

    By “reverse engineering the fastest growing company in the history of the world,” author Jeff Jarvis, proprietor of Buzzmachine.com, one of the Web’s most widely respected media blogs, offers indispensible strategies for solving the toughest new problems facing businesses today. With a new afterword from the author, What Would Google Do? is the business book that every leader or potential leader in every industry must read.

    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

    One of the most coveted tools in a spy's arsenal, a zero day has the power to silently spy on your iPhone, dismantle the safety controls at a chemical plant, alter an election, and shut down the electric grid (just ask Ukraine).For decades, under cover of classification levels and non-disclosure agreements, the United States government became the world's dominant hoarder of zero days. U.S. government agents paid top dollar-first thousands, and later millions of dollars- to hackers willing to sell their lock-picking code and their silence. Then the United States lost control of its hoard and the market. Now those zero days are in the hands of hostile nations and mercenaries who do not care if your vote goes missing, your clean water is contaminated, or our nuclear plants melt down.Filled with spies, hackers, arms dealers, and a few unsung heroes, written like a thriller and a reference, This Is How They Tell Me the World Ends is an astonishing feat of journalism. Based on years of reporting and hundreds of interviews, The New York Times reporter Nicole Perlroth lifts the curtain on a market in shadow, revealing the urgent threat faced by us all if we cannot bring the global cyber arms race to heel.

    But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.

    This comprehensive work covers both statistical and symbolic approaches to language processing; it shows how they can be applied to important tasks such as speech recognition, spelling and grammar correction, information extraction, search engines, machine translation, and the creation of spoken-language dialog agents. The following distinguishing features make the text both an introduction to the field and an advanced reference guide.- UNIFIED AND COMPREHENSIVE COVERAGE OF THE FIELDCovers the fundamental algorithms of each field, whether proposed for spoken or written language, whether logical or statistical in origin.- EMPHASIS ON WEB AND OTHER PRACTICAL APPLICATIONSGives readers an understanding of how language-related algorithms can be applied to important real-world problems.- EMPHASIS ON SCIENTIFIC EVALUATIONOffers a description of how systems are evaluated with each problem domain.- EMPERICIST/STATISTICAL/MACHINE LEARNING APPROACHES TO LANGUAGE PROCESSINGCovers all the new statistical approaches, while still completely covering the earlier more structured and rule-based methods.

    Mirroring his theory, Minsky boldly casts The Society of Mind as an intellectual puzzle whose pieces are assembled along the way. Each chapter -- on a self-contained page -- corresponds to a piece in the puzzle. As the pages turn, a unified theory of the mind emerges, like a mosaic. Ingenious, amusing, and easy to read, The Society of Mind is an adventure in imagination.

    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data

    But what if you could have your computer do them for you?In "Automate the Boring Stuff with Python," you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to: Search for text in a file or across multiple filesCreate, update, move, and rename files and foldersSearch the Web and download online contentUpdate and format data in Excel spreadsheets of any sizeSplit, merge, watermark, and encrypt PDFsSend reminder emails and text notificationsFill out online formsStep-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in "Automate the Boring Stuff with Python.""

    This might seem uncontroversial, but it flies in the face of a tech sector long obsessed with rapid growth and sometimes on disruption as an end in itself. Now, though, we have reached an inflection point: Silicon Valley has moved fast and it has broken things. A new understanding has emerged that companies that create technology must accept greater responsibility for the future. And governments will need to regulate technology by moving faster and catching up with the pace of innovation that is impacting our communities and changing the world.In Tools and Weapons, Brad Smith takes us into the cockpit of one of the world's largest and most powerful tech companies as it finds itself in the middle of some of the thorniest emerging issues of our time. These are challenges that come with no preexisting playbook, including privacy, cybercrime and cyberwar, social media, the moral conundrums of AI, big tech's relationship to inequality and the challenges for democracy, far and near. While in no way a self-glorifying "Microsoft memoir," the book opens up the curtain remarkably wide onto some of the company's most crucial recent decision points, as it strives to protect the hopes technology offers against the very real threats it also presents. Every tool can be a weapon in the wrong person's hands, and companies are being challenged in entirely new ways to embrace the totality of their responsibilities. We have moved from a world in which Silicon Valley could take no prisoners to one in which tech companies and governments must work together to address the challenges and adapt to the changes technology has unleashed. There are huge ramifications to be thought through, and Brad Smith provides a marvelous and urgently necessary contribution to that effort.

    But what is it physically? And where is it really? Our mental map of the network is as blank as the map of the ocean that Columbus carried on his first Atlantic voyage. The Internet, its material nuts and bolts, is an unexplored territory. Until now.In Tubes, journalist Andrew Blum goes inside the Internet's physical infrastructure and flips on the lights, revealing an utterly fresh look at the online world we think we know. It is a shockingly tactile realm of unmarked compounds, populated by a special caste of engineer who pieces together our networks by hand; where glass fibers pulse with light and creaky telegraph buildings, tortuously rewired, become communication hubs once again. From the room in Los Angeles where the Internet first flickered to life to the caverns beneath Manhattan where new fiber-optic cable is buried; from the coast of Portugal, where a ten-thousand-mile undersea cable just two thumbs wide connects Europe and Africa, to the wilds of the Pacific Northwest, where Google, Microsoft, and Facebook have built monumental data centers—Blum chronicles the dramatic story of the Internet's development, explains how it all works, and takes the first-ever in-depth look inside its hidden monuments.This is a book about real places on the map: their sounds and smells, their storied pasts, their physical details, and the people who live there. For all the talk of the "placelessness" of our digital age, the Internet is as fixed in real, physical spaces as the railroad or telephone. You can map it and touch it, and you can visit it. Is the Internet in fact "a series of tubes" as Ted Stevens, the late senator from Alaska, once famously described it? How can we know the Internet's possibilities if we don't know its parts?Like Tracy Kidder's classic The Soul of a New Machine or Tom Vanderbilt's recent bestseller Traffic, Tubes combines on-the-ground reporting and lucid explanation into an engaging, mind-bending narrative to help us understand the physical world that underlies our digital lives.

    These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of Web intelligence, as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected.Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.