Book picks similar to
Big Data: Does Size Matter? by Timandra Harkness
science
nonfiction
non-fiction
tech
Chaos Monkeys: Obscene Fortune and Random Failure in Silicon Valley
Antonio García Martínez - 2016
Infrastructure engineers use a software version of this “chaos monkey” to test online services’ robustness—their ability to survive random failure and correct mistakes before they actually occur. Tech entrepreneurs are society’s chaos monkeys, disruptors testing and transforming every aspect of our lives, from transportation (Uber) and lodging (AirBnB) to television (Netflix) and dating (Tinder). One of Silicon Valley’s most audacious chaos monkeys is Antonio García Martínez.After stints on Wall Street and as CEO of his own startup, García Martínez joined Facebook’s nascent advertising team, turning its users’ data into profit for COO Sheryl Sandberg and chairman and CEO Mark “Zuck” Zuckerberg. Forced out in the wake of an internal product war over the future of the company’s monetization strategy, García Martínez eventually landed at rival Twitter. He also fathered two children with a woman he barely knew, committed lewd acts and brewed illegal beer on the Facebook campus (accidentally flooding Zuckerberg's desk), lived on a sailboat, raced sport cars on the 101, and enthusiastically pursued the life of an overpaid Silicon Valley wastrel.Now, this gleeful contrarian unravels the chaotic evolution of social media and online marketing and reveals how it is invading our lives and shaping our future. Weighing in on everything from startups and credit derivatives to Big Brother and data tracking, social media monetization and digital “privacy,” García Martínez shares his scathing observations and outrageous antics, taking us on a humorous, subversive tour of the fascinatingly insular tech industry. Chaos Monkeys lays bare the hijinks, trade secrets, and power plays of the visionaries, grunts, sociopaths, opportunists, accidental tourists, and money cowboys who are revolutionizing our world. The question is, will we survive?
Superintelligence: Paths, Dangers, Strategies
Nick Bostrom - 2014
The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. If machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful--possibly beyond our control. As the fate of the gorillas now depends more on humans than on the species itself, so would the fate of humankind depend on the actions of the machine superintelligence.But we have one advantage: we get to make the first move. Will it be possible to construct a seed Artificial Intelligence, to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation?
Power to the Public: The Promise of Public Interest Technology
Tara Dawson McGuinness - 2021
In Power to the Public, Tara Dawson McGuinness and Hana Schank describe a revolutionary new approach--public interest technology--that has the potential to transform the way governments and nonprofits around the world solve problems. Through inspiring stories about successful projects ranging from a texting service for teenagers in crisis to a streamlined foster care system, the authors show how public interest technology can make the delivery of services to the public more effective and efficient.At its heart, public interest technology means putting users at the center of the policymaking process, using data and metrics in a smart way, and running small experiments and pilot programs before scaling up. And while this approach may well involve the innovative use of digital technology, technology alone is no panacea--and some of the best solutions may even be decidedly low-tech.Clear-eyed yet profoundly optimistic, Power to the Public presents a powerful blueprint for how government and nonprofits can help solve society's most serious problems.
The Idea Factory: Bell Labs and the Great Age of American Innovation
Jon Gertner - 2012
From the transistor to the laser, it s hard to find an aspect of modern life that hasn t been touched by Bell Labs. Why did so many transformative ideas come from Bell Labs? In "The Idea Factory," Jon Gertner traces the origins of some of the twentieth century s most important inventions and delivers a riveting and heretofore untold chapter of American history. At its heart this is a story about the life and work of a small group of brilliant and eccentric men Mervin Kelly, Bill Shockley, Claude Shannon, John Pierce, and Bill Baker who spent their careers at Bell Labs. Their job was to research and develop the future of communications. Small-town boys, childhood hobbyists, oddballs: they give the lie to the idea that Bell Labs was a grim cathedral of top-down command and control.Gertner brings to life the powerful alchemy of the forces at work behind Bell Labs inventions, teasing out the intersections between science, business, and society. He distills the lessons that abide: how to recruit and nurture young talent; how to organize and lead fractious employees; how to find solutions to the most stubbornly vexing problems; how to transform a scientific discovery into a marketable product, then make it even better, cheaper, or both. Today, when the drive to invent has become a mantra, Bell Labs offers us a way to enrich our understanding of the challenges and solutions to technological innovation. Here, after all, was where the foundational ideas on the management of innovation were born. "The Idea Factory" is the story of the origins of modern communications and the beginnings of the information age a deeply human story of extraordinary men who were given extraordinary means time, space, funds, and access to one another and edged the world into a new dimension."
The Hundred-Page Machine Learning Book
Andriy Burkov - 2019
During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.
Python for Data Analysis
Wes McKinney - 2011
It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
Machine Learning: A Probabilistic Perspective
Kevin P. Murphy - 2012
Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
Dreaming in Code: Two Dozen Programmers, Three Years, 4,732 Bugs, and One Quest for Transcendent Software
Scott Rosenberg - 2007
Along the way, we encounter black holes, turtles, snakes, dragons, axe-sharpening, and yak-shaving—and take a guided tour through the theories and methods, both brilliant and misguided, that litter the history of software development, from the famous ‘mythical man-month’ to Extreme Programming. Not just for technophiles but for anyone captivated by the drama of invention, Dreaming in Code offers a window into both the information age and the workings of the human mind.
Web Analytics 2.0: The Art of Online Accountability & Science of Customer Centricity [With CDROM]
Avinash Kaushik - 2009
"Web Analytics 2.0" presents a new framework that will permanently change how you think about analytics. It provides specific recommendations for creating an actionable strategy, applying analytical techniques correctly, solving challenges such as measuring social media and multichannel campaigns, achieving optimal success by leveraging experimentation, and employing tactics for truly listening to your customers. The book will help your organization become more data driven while you become a super analysis ninja Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
The Fuzzy and the Techie: Why the Liberal Arts Will Rule the Digital World
Scott Hartley - 2017
If you majored in the humanities or social sciences, you were a fuzzy. If you majored in the computer sciences, you were a techie. This informal division has quietly found its way into a default assumption that has mistakenly led the business world for decades: that techies are the real drivers of innovation.But in this brilliantly contrarian book, Hartley reveals the counterintuitive reality of business today: it's actually the fuzzies-not the techies-who are playing the key roles in developing the most creative and successful new business ideas. They are often the ones who understand the life issues that need solving and offer the best approaches for doing so. They also bring the management and communication skills that are so vital to spurring growth.Hartley looks inside some of today's most dynamic new companies, reveals breakthrough fuzzy-techie collaborations, and explores how such collaborations work to create real innovation.
The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do
Erik J. Larson - 2021
What hope do we have against superintelligent machines? But we aren't really on the path to developing intelligent machines. In fact, we don't even know where that path might be.A tech entrepreneur and pioneering research scientist working at the forefront of natural language processing, Erik Larson takes us on a tour of the landscape of AI to show how far we are from superintelligence, and what it would take to get there. Ever since Alan Turing, AI enthusiasts have equated artificial intelligence with human intelligence. This is a profound mistake. AI works on inductive reasoning, crunching data sets to predict outcomes. But humans don't correlate data sets: we make conjectures informed by context and experience. Human intelligence is a web of best guesses, given what we know about the world. We haven't a clue how to program this kind of intuitive reasoning, known as abduction. Yet it is the heart of common sense. That's why Alexa can't understand what you are asking, and why AI can only take us so far.Larson argues that AI hype is both bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we want to make real progress, we will need to start by more fully appreciating the only true intelligence we know--our own.
The Black Box Society: The Secret Algorithms That Control Money and Information
Frank Pasquale - 2014
The data compiled and portraits created are incredibly detailed, to the point of being invasive. But who connects the dots about what firms are doing with this information? The Black Box Society argues that we all need to be able to do so--and to set limits on how big data affects our lives.Hidden algorithms can make (or ruin) reputations, decide the destiny of entrepreneurs, or even devastate an entire economy. Shrouded in secrecy and complexity, decisions at major Silicon Valley and Wall Street firms were long assumed to be neutral and technical. But leaks, whistleblowers, and legal disputes have shed new light on automated judgment. Self-serving and reckless behavior is surprisingly common, and easy to hide in code protected by legal and real secrecy. Even after billions of dollars of fines have been levied, underfunded regulators may have only scratched the surface of this troubling behavior.Frank Pasquale exposes how powerful interests abuse secrecy for profit and explains ways to rein them in. Demanding transparency is only the first step. An intelligible society would assure that key decisions of its most important firms are fair, nondiscriminatory, and open to criticism. Silicon Valley and Wall Street need to accept as much accountability as they impose on others.
Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
Matthew A. Russell - 2011
You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.Get a straightforward synopsis of the social web landscapeUse adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+Learn how to employ easy-to-use Python tools to slice and dice the data you collectExplore social connections in microformats with the XHTML Friends NetworkApply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detectionBuild interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google
The Social Life of Information
John Seely Brown - 2000
John Seely Brown and Paul Duguid argue that the gap between digerati hype and end-user gloom is largely due to the "tunnel vision" that information-driven technologies breed. We've become so focused on where we think we ought to be--a place where technology empowers individuals and obliterates social organizations--that we often fail to see where we're really going.The Social Life of Information shows us how to look beyond our obsession with information and individuals to include the critical social networks of which these are always a part.
The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future
Kevin Kelly - 2016
In this fascinating, provocative new book, Kevin Kelly provides an optimistic road map for the future, showing how the coming changes in our lives—from virtual reality in the home to an on-demand economy to artificial intelligence embedded in everything we manufacture—can be understood as the result of a few long-term, accelerating forces. Kelly both describes these deep trends—flowing, screening, accessing, sharing, filtering, remixing, tracking, and questioning—and demonstrates how they overlap and are codependent on one another. These larger forces will completely revolutionize the way we buy, work, learn, and communicate with each other. By understanding and embracing them, says Kelly, it will be easier for us to remain on top of the coming wave of changes and to arrange our day-to-day relationships with technology in ways that bring forth maximum benefits. Kelly’s bright, hopeful book will be indispensable to anyone who seeks guidance on where their business, industry, or life is heading—what to invent, where to work, in what to invest, how to better reach customers, and what to begin to put into place—as this new world emerges.