What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us.In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

    If you're looking for a book like that, put this one back on the shelf.Rework shows you a better, faster, easier way to succeed in business. Read it and you'll know why plans are actually harmful, why you don't need outside investors, and why you're better off ignoring the competition. The truth is, you need less than you think. You don't need to be a workaholic. You don't need to staff up. You don't need to waste time on paperwork or meetings. You don't even need an office. Those are all just excuses.  What you really need to do is stop talking and start working. This book shows you the way. You'll learn how to be more productive, how to get exposure without breaking the bank, and tons more counterintuitive ideas that will inspire and provoke you.With its straightforward language and easy-is-better approach, Rework is the perfect playbook for anyone who’s ever dreamed of doing it on their own. Hardcore entrepreneurs, small-business owners, people stuck in day jobs they hate, victims of "downsizing," and artists who don’t want to starve anymore will all find valuable guidance in these pages.

    The findings will surprise many readers and, quite frankly, upset others.The ChallengeBuilt to Last, the defining management study of the nineties, showed how great companies triumph over time and how long-term sustained performance can be engineered into the DNA of an enterprise from the very beginning. But what about the company that is not born with great DNA? How can good companies, mediocre companies, even bad companies achieve enduring greatness? The StudyFor years, this question preyed on the mind of Jim Collins. Are there companies that defy gravity and convert long-term mediocrity or worse into long-term superiority? And if so, what are the universal distinguishing characteristics that cause a company to go from good to great?The StandardsUsing tough benchmarks, Collins and his research team identified a set of elite companies that made the leap to great results and sustained those results for at least fifteen years. How great? After the leap, the good-to-great companies generated cumulative stock returns that beat the general stock market by an average of seven times in fifteen years, better than twice the results delivered by a composite index of the world's greatest companies, including Coca-Cola, Intel, General Electric, and Merck. The ComparisonsThe research team contrasted the good-to-great companies with a carefully selected set of comparison companies that failed to make the leap from good to great. What was different? Why did one set of companies become truly great performers while the other set remained only good? The FindingsThe findings of the Good to Great study will surprise many readers and shed light on virtually every area of management strategy and practice. The findings include:Level 5 Leaders: The research team was shocked to discover the type of leadership required to achieve greatness.The Hedgehog Concept (Simplicity within the Three Circles): To go from good to great requires transcending the curse of competence.A Culture of Discipline: When you combine a culture of discipline with an ethic of entrepreneurship, you get the magical alchemy of great results. Technology Accelerators: Good-to-great companies think differently about the role of technology.The Flywheel and the Doom Loop: Those who launch radical change programs and wrenching restructurings will almost certainly fail to make the leap.

    AIQ explores the fascinating history of the ideas that drive this technology of the future and demystifies the core concepts behind it; the result is a positive and entertaining look at the great potential unlocked by marrying human creativity with powerful machines.” —Steven D. Levitt, bestselling co-author of Freakonomics From leading data scientists Nick Polson and James Scott, what everyone needs to know to understand how artificial intelligence is changing the world and how we can use this knowledge to make better decisions in our own lives. Dozens of times per day, we all interact with intelligent machines that are constantly learning from the wealth of data now available to them. These machines, from smart phones to talking robots to self-driving cars, are remaking the world in the 21st century in the same way that the Industrial Revolution remade the world in the 19th century. AIQ is based on a simple premise: if you want to understand the modern world, then you have to know a little bit of the mathematical language spoken by intelligent machines. AIQ will teach you that language—but in an unconventional way, anchored in stories rather than equations. You will meet a fascinating cast of historical characters who have a lot to teach you about data, probability, and better thinking. Along the way, you'll see how these same ideas are playing out in the modern age of big data and intelligent machines—and how these technologies will soon help you to overcome some of your built-in cognitive weaknesses, giving you a chance to lead a happier, healthier, more fulfilled life.

    It took the open source world by storm since its inception in 2005, and is used by small development shops and giants like Google, Red Hat, and IBM, and of course many open source projects.A book by Git experts to turn you into a Git expert. Introduces the world of distributed version control Shows how to build a Git development workflow.

    Simply by designing your product the right way, you can build a flourishing business from scratch. No advertising or marketing budget, no need for a sales force, and venture capitalists will flock to throw money at you. Many of the most successful Web 2.0 companies, including MySpace, YouTube, eBay, and rising stars like Twitter and Flickr, are prime examples of what journalist Adam L. Penenberg calls a "viral loop"--to use it, you have to spread it. After all, what's the sense of being on Facebook if none of your friends are? The result: Never before has there been the potential to create wealth this fast, on this scale, and starting with so little. In this game-changing must-read, Penenberg tells the fascinating story of the entrepreneurs who first harnessed the unprecedented potential of viral loops to create the successful online businesses--some worth billions of dollars--that we have all grown to rely on. The trick is that they created something people really want, so much so that their customers happily spread the word about their product for them. All kinds of businesses--from the smallest start-ups to nonprofit organizations to the biggest multinational corporations--can use the paradigm-busting power of viral loops to enable their business through technology. Viral Loop is a must-read for any entrepreneur or business interested in uncorking viral loops to benefit their bottom line.

    

    The Google Story takes you deep inside the company's wild ride from an idea that struggled for funding in 1998 to a firm that rakes in billions in profits, making Brin and Page the wealthiest young men in America. Based on scrupulous research and extraordinary access to Google, this fast-moving narrative reveals how an unorthodox management style and culture of innovation enabled a search engine to shake up Madison Avenue and Wall Street, scoop up YouTube, and battle Microsoft at every turn. Not afraid of controversy, Google is expanding in Communist China and quietly working on a searchable genetic database, initiatives that test the founders' guiding mantra: DON'T BE EVIL.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    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.

    In its sweeping survey of the history of Internet search technologies, its gossip about and analysis of Google, and its speculation on the larger cultural implications of a Web-connected world, it will likely receive attention from a variety of businesspeople, technology futurists, journalists, and interested observers of mid-2000s zeitgeist. This ambitious book comes with a strong pedigree. Author John Battelle was a founder of The Industry Standard and then one of the original editors of Wired, two magazines which helped shape our early perceptions of the wild world of the Internet. Battelle clearly drew from his experience and contacts in writing The Search. In addition to the sure-handed historical perspective and easy familiarity with such dot-com stalwarts as AltaVista, Lycos, and Excite, he speckles his narrative with conversational asides from a cast of fascinating characters, such Google's founders, Larry Page and Sergey Brin; Yahoo's, Jerry Yang and David Filo; key executives at Microsoft and different VC firms on the famed Sandhill road; and numerous other insiders, particularly at the company which currently sits atop the search world, Google. The Search is not exactly the corporate history of Google. At the book's outset, Battelle specifically indicates his desire to understand what he calls the cultural anthropology of search, and to analyze search engines' current role as the "database of our intentions"--the repository of humanity's curiosity, exploration, and expressed desires. Interesting though that beginning is, though, Battelle's story really picks up speed when he starts dishing inside scoop on the darling business story of the decade, Google. To Battelle's credit, though, he doesn't stop just with historical retrospective: the final part of his book focuses on the potential future directions of Google and its products' development. In what Battelle himself acknowledges might just be a "digital fantasy train", he describes the possibility that Google will become the centralizing platform for our entire lives and quotes one early employee on the weightiness of Google's potential impact: "Sometimes I feel like I am on a bridge, twenty thousand feet up in the air. If I look down I'm afraid I'll fall. I don't feel like I can think about all the implications." Some will shrug at such words; after all, similar hype has accompanied other technologies and other companies before. Many others, though, will search Battelle's story for meaning--and fast. --Peter Han

    But its visionary founder, Jeff Bezos, wasn't content with being a bookseller. He wanted Amazon to become the everything store, offering limitless selection and seductive convenience at disruptively low prices. To do so, he developed a corporate culture of relentless ambition and secrecy that's never been cracked. Until now. Brad Stone enjoyed unprecedented access to current and former Amazon employees and Bezos family members, giving readers the first in-depth, fly-on-the-wall account of life at Amazon. Compared to tech's other elite innovators--Jobs, Gates, Zuckerberg--Bezos is a private man. But he stands out for his restless pursuit of new markets, leading Amazon into risky new ventures like the Kindle and cloud computing, and transforming retail in the same way Henry Ford revolutionized manufacturing.The Everything Store will be the revealing, definitive biography of the company that placed one of the first and largest bets on the Internet and forever changed the way we shop and read.

    According to the August Forrester Report, 56 percent of IT managers interviewed at Global 2,500 companies are already using some type of open source software in their infrastructure and another 6 percent will install it in the next two years. This revolutionary model for collaborative software development is being embraced and studied by many of the biggest players in the high-tech industry, from Sun Microsystems to IBM to Intel.The Cathedral & the Bazaar is a must for anyone who cares about the future of the computer industry or the dynamics of the information economy. Already, billions of dollars have been made and lost based on the ideas in this book. Its conclusions will be studied, debated, and implemented for years to come. According to Bob Young, "This is Eric Raymond's great contribution to the success of the open source revolution, to the adoption of Linux-based operating systems, and to the success of open source users and the companies that supply them."The interest in open source software development has grown enormously in the past year. This revised and expanded paperback edition includes new material on open source developments in 1999 and 2000. Raymond's clear and effective writing style accurately describing the benefits of open source software has been key to its success. With major vendors creating acceptance for open source within companies, independent vendors will become the open source story in 2001.

    It seems hard to believe today, but there was a time when Airbnb was the best-kept secret of travel hackers and couch surfers, Pinterest was a niche web site frequented only by bakers and crafters, LinkedIn was an exclusive network for C-suite executives and top-level recruiters, Facebook was MySpace's sorry step-brother, and Uber was a scrappy upstart that didn't stand a chance against the Goliath that was New York City Yellow Cabs.So how did these companies grow from these humble beginnings into the powerhouses they are today? Contrary to popular belief, they didn't explode to massive worldwide popularity simply by building a great product then crossing their fingers and hoping it would catch on. There was a studied, carefully implemented methodology behind these companies' extraordinary rise. That methodology is called Growth Hacking, and it's practitioners include not just today's hottest start-ups, but also companies like IBM, Walmart, and Microsoft as well as the millions of entrepreneurs, marketers, managers and executives who make up the community of GrowthHackers.com.Think of the Growth Hacking methodology as doing for market-share growth what Lean Start-Up did for product development, and Scrum did for productivity. It involves cross-functional teams and rapid-tempo testing and iteration that focuses customers attaining them, retaining them, engaging them, and motivating them to come back and buy more. An accessible and practical toolkit that teams and companies in all industries can use to increase their customer base and market share, this book walks readers through the process of creating and executing their own custom-made growth hacking strategy. It is a must read for any marketer, entrepreneur, innovator or manger looking to replace wasteful big bets and "spaghetti-on-the-wall" approaches with more consistent, replicable, cost-effective, and data-driven results.

    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.