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Black Code: Inside the Battle for Cyberspace
Robert J. Deibert - 2013
We depend on it for everything we do. We have reengineered our business, governance, and social relations around a planetary network unlike any before it. But there are dangers looming, and malign forces are threatening to transform this extraordinary domain.In Black Code, Ronald J. Deibert, a leading expert on digital technology, security, and human rights, lifts the lid on cyberspace and shows what’s at stake for Internet users and citizens. As cyberspace develops in unprecedented ways, powerful agents are scrambling for control. Predatory cyber criminal gangs such as Koobface have made social media their stalking ground. The discovery of Stuxnet, a computer worm reportedly developed by Israel and the United States and aimed at Iran’s nuclear facilities, showed that state cyberwar is now a very real possibility. Governments and corporations are in collusion and are setting the rules of the road behind closed doors.This is not the way it was supposed to be. The Internet’s original promise of a global commons of shared knowledge and communications is now under threat. Drawing on the first-hand experiences of one of the most important protagonists in the battle — the Citizen Lab and its global network of frontline researchers, who have spent more than a decade cracking cyber espionage rings and uncovering attacks on citizens and NGOs worldwide — Black Code takes readers on a fascinating journey into the battle for cyberspace. Thought-provoking, compelling, and sometimes frightening, it is a wakeup call to citizens who have come to take the Internet for granted. Cyberspace is ours, it is what we make of it, Deibert argues, and we need to act now before it slips through our grasp.
System Software: An Introduction to Systems Programming
Leland L. Beck - 1985
Stressing the relationship between system software and the architecture of the machine it is designed to support, Beck first presents the fundamental concepts and basic design of each type of software in a machine-independent way. He then discusses both machine-dependent and independent extensions to the basic concepts, and gives examples of the actual system software. New FeaturesProvides updated architecture and software examples, including the Intel x86 family (Pentium, P6, etc.), IBM PowerPC, Sun SPARC, and Cray T3E. Includes an introduction to object-oriented programming and design, and illustrates these concepts of object-oriented languages, compilers, and operating systems. Brings the book up-to-speed with industry by including current operating systems topics, such as multiprocessor, distributed, and client/server systems. Contains a wide selection of examples and exercises, providing teaching support as well as flexibility, allowing you to concentrate on the software and architectures that you want to cover.
Think Like a Programmer: An Introduction to Creative Problem Solving
V. Anton Spraul - 2012
In this one-of-a-kind text, author V. Anton Spraul breaks down the ways that programmers solve problems and teaches you what other introductory books often ignore: how to Think Like a Programmer. Each chapter tackles a single programming concept, like classes, pointers, and recursion, and open-ended exercises throughout challenge you to apply your knowledge. You'll also learn how to:Split problems into discrete components to make them easier to solve Make the most of code reuse with functions, classes, and libraries Pick the perfect data structure for a particular job Master more advanced programming tools like recursion and dynamic memory Organize your thoughts and develop strategies to tackle particular types of problems Although the book's examples are written in C++, the creative problem-solving concepts they illustrate go beyond any particular language; in fact, they often reach outside the realm of computer science. As the most skillful programmers know, writing great code is a creative art—and the first step in creating your masterpiece is learning to Think Like a Programmer.
Concrete Mathematics: A Foundation for Computer Science
Ronald L. Graham - 1988
"More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."
R for Dummies
Joris Meys - 2012
R is packed with powerful programming capabilities, but learning to use R in the real world can be overwhelming for even the most seasoned statisticians. This easy-to-follow guide explains how to use R for data processing and statistical analysis, and then, shows you how to present your data using compelling and informative graphics. You'll gain practical experience using R in a variety of settings and delve deeper into R's feature-rich toolset.Includes tips for the initial installation of RDemonstrates how to easily perform calculations on vectors, arrays, and lists of dataShows how to effectively visualize data using R's powerful graphics packagesGives pointers on how to find, install, and use add-on packages created by the R communityProvides tips on getting additional help from R mailing lists and websitesWhether you're just starting out with statistical analysis or are a procedural programming pro, "R For Dummies" is the book you need to get the most out of R.
Surviving AI: The promise and peril of artificial intelligence
Calum Chace - 2015
If we get it right it will make humans almost godlike. If we get it wrong... well, extinction is not the worst possible outcome.“Surviving AI” is a concise, easy-to-read guide to what's coming, taking you through technological unemployment (the economic singularity) and the possible creation of a superintelligence (the technological singularity).Here's what some of the leading thinkers in the field have to say about it:A sober and easy-to-read review of the risks and opportunities that humanity will face from AI. Jaan Tallinn – co-founder of Skype Understanding AI – its promise and its dangers – is emerging as one of the great challenges of coming decades and this is an invaluable guide to anyone who’s interested, confused, excited or scared. David Shukman – BBC Science Editor We have recently seen a surge in the volume of scholarly analysis of this topic; Chace impressively augments that with this high-quality, more general-audience discussion. Aubrey de Grey – CSO of SENS Research Foundation; former AI researcher It's rare to see a book about the potential End of the World that is fun to read without descending into sensationalism or crass oversimplification. Ben Goertzel – chairman of Novamente LLC Calum Chace is a prescient messenger of the risks and rewards of artificial intelligence. In “Surviving AI” he has identified the most essential issues and developed them with insight and wit – so that the very framing of the questions aids our search for answers. Chace’s sensible balance between AI’s promise and peril makes “Surviving AI” an excellent primer for anyone interested in what’s happening, how we got here, and where we are headed. Kenneth Cukier – co-author of “Big Data” If you’re not thinking about AI, you’re not thinking. “Surviving AI” combines an essential grounding in the state of the art with a survey of scenarios that will be discussed with equal vigor at cocktail parties and academic colloquia. Chris Meyer – author of “Blur”, “It’s Alive”, and “Standing on the Sun” The appearance of Calum Chace's book is of some considerable personal satisfaction to me, because it signifies the fact that the level of social awareness of the rise of massively intelligent machines has finally reached the mainstream. If you want to survive the next few decades, you cannot afford NOT to read Chace's book. Prof. Dr. Hugo de Garis – former director of the Artificial Brain Lab, Xiamen University, China “Surviving AI” is an exceptionally clear, well-researched and balanced introduction to a complex and controversial topic, and is a compelling read to boot. Seán Ó hÉigeartaigh – executive director of Cambridge Centre for the Study of Existential Risk In “Surviving AI”, Calum Chace provides a marvellously accessible guide to the swirls of controversy that surround discussion of what is likely to be the single most important event in human history - the emergence of artificial super
PCs for Dummies
Dan Gookin - 1992
They have also sprouted new and wondrous capabilities at a dizzying pace. This 11th Edition of the all-time bestselling PC guide has been polished and honed to deliver everything you need to know about your twenty-first-century PC -- from what plugs into what to adjusting your monitor to burning DVDs, and much more.Whether you want to go online, install a firewall, live the digital life, or finally get a handle on the whole computer software concept, this fun, plain-English handbook is here to answer all your questions PC questions. You'll find out why Windows Vista is the way to go and how to use it to get everywhere else. And, you'll pick up Web and email tricks and learn about all the new levels of PC security. Discover how to: Set up your PC Use Vista menus Store your stuff on Memory Cards Record live TV Download digital photos Connect to a wireless network Explore the Internet safely Print perfect documents, photos, and more Use your PC as the new hub of your digital worldComplete with helpful hints on how to avoid beginner mistakes, a list of extras and accessories you may want for your PC, and insider tips from a PC guru. PCs for Dummies, 11th Edition is the one PC accessory you can't do without.
Designing Data-Intensive Applications
Martin Kleppmann - 2015
Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Big Data Now: Current Perspectives from O'Reilly Radar
O'Reilly Radar Team - 2011
Mike Loukides kicked things off in June 2010 with “What is data science?” and from there we’ve pursued the various threads and themes that naturally emerged. Now, roughly a year later, we can look back over all we’ve covered and identify a number of core data areas: Data issues -- The opportunities and ambiguities of the data space are evident in discussions around privacy, the implications of data-centric industries, and the debate about the phrase “data science” itself. The application of data: products and processes – A “data product” can emerge from virtually any domain, including everything from data startups to established enterprises to media/journalism to education and research. Data science and data tools -- The tools and technologies that drive data science are of course essential to this space, but the varied techniques being applied are also key to understanding the big data arena.The business of data – Take a closer look at the actions connected to data -- the finding, organizing, and analyzing that provide organizations of all sizes with the information they need to compete.
Structure and Interpretation of Computer Programs
Harold Abelson - 1984
This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.
Data Driven
D.J. Patil - 2015
It requires you to develop a data culture that involves people throughout the organization. In this O’Reilly report, DJ Patil and Hilary Mason outline the steps you need to take if your company is to be truly data-driven—including the questions you should ask and the methods you should adopt.
You’ll not only learn examples of how Google, LinkedIn, and Facebook use their data, but also how Walmart, UPS, and other organizations took advantage of this resource long before the advent of Big Data. No matter how you approach it, building a data culture is the key to success in the 21st century.
You’ll explore:
Data scientist skills—and why every company needs a Spock
How the benefits of giving company-wide access to data outweigh the costs
Why data-driven organizations use the scientific method to explore and solve data problems
Key questions to help you develop a research-specific process for tackling important issues
What to consider when assembling your data team
Developing processes to keep your data team (and company) engaged
Choosing technologies that are powerful, support teamwork, and easy to use and learn
The Book of Why: The New Science of Cause and Effect
Judea Pearl - 2018
Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.
The Game Maker's Apprentice: Game Development for Beginners
Jacob Habgood - 2006
This book covers a range of genres, including action, adventure, and puzzle games complete with professional quality sound effects and visuals. It discusses game design theory and features practical examples of how this can be applied to making games that are more fun to play. Game Maker allows games to be created using a simple drag-and-drop interface, so you don't need to have any prior coding experience. It includes an optional programming language for adding advanced features to your games, when you feel ready to do so. You can obtain more information by visiting book.gamemaker.nl. The authors include the creator of the Game Maker tool and a former professional game programmer, so you'll glean understanding from their expertise. The book also includes a DVD containing Game Maker software and all of the game projects that are created in the book—plus a host of professional-quality graphics and sound effects that you can use in your own games.
The Creativity Code: How AI Is Learning to Write, Paint and Think
Marcus du Sautoy - 2019
They can navigate more data than a doctor or lawyer and act with greater precision. For many years we’ve taken solace in the notion that they can’t create. But now that algorithms can learn and adapt, does the future of creativity belong to machines, too?It is hard to imagine a better guide to the bewildering world of artificial intelligence than Marcus du Sautoy, a celebrated Oxford mathematician whose work on symmetry in the ninth dimension has taken him to the vertiginous edge of mathematical understanding. In The Creativity Code he considers what machine learning means for the future of creativity. The Pollockizer can produce drip paintings in the style of Jackson Pollock, Botnik spins off fanciful (if improbable) scenes inspired by J. K. Rowling, and the music-composing algorithm Emmy managed to fool a panel of Bach experts. But do these programs just mimic, or do they have what it takes to create? Du Sautoy argues that to answer this question, we need to understand how the algorithms that drive them work―and this brings him back to his own subject of mathematics, with its puzzles, constraints, and enticing possibilities.While most recent books on AI focus on the future of work, The Creativity Code moves us to the forefront of creative new technologies and offers a more positive and unexpected vision of our future cohabitation with machines. It challenges us to reconsider what it means to be human―and to crack the creativity code.
Data Points: Visualization That Means Something
Nathan Yau - 2013
In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data.Shares intriguing ideas from Nathan Yau, author of Visualize This and creator of flowingdata.com, with over 66,000 subscribers Focuses on visualization, data graphics that help viewers see trends and patterns they might not otherwise see in a table Includes examples from the author's own illustrations, as well as from professionals in statistics, art, design, business, computer science, cartography, and more Examines standard rules across all visualization applications, then explores when and where you can break those rules Create visualizations that register at all levels, with Data Points: Visualization That Means Something.