Stay in the know, spot trends as they happen, and push your business to new limits. This e-book introduces Microsoft Power BI basics through a practical, scenario-based guided tour of the tool, showing you how to build analytical solutions using Power BI. Get an overview of Power BI, or dig deeper and follow along on your PC using the book's examples.

    It also works beautifully with other open source tools, such as the MySQL database and the Apache web server. However, as more web sites are developed in PHP, they become targets for malicious attackers, and developers need to prepare for the attacks.Security is an issue that demands attention, given the growing frequency of attacks on web sites. Essential PHP Security explains the most common types of attacks and how to write code that isn't susceptible to them. By examining specific attacks and the techniques used to protect against them, you will have a deeper understanding and appreciation of the safeguards you are about to learn in this book.In the much-needed (and highly-requested) Essential PHP Security, each chapter covers an aspect of a web application (such as form processing, database programming, session management, and authentication). Chapters describe potential attacks with examples and then explain techniques to help you prevent those attacks.Topics covered include:Preventing cross-site scripting (XSS) vulnerabilitiesProtecting against SQL injection attacksComplicating session hijacking attemptsYou are in good hands with author Chris Shiflett, an internationally-recognized expert in the field of PHP security. Shiflett is also the founder and President of Brain Bulb, a PHP consultancy that offers a variety of services to clients around the world.

    The new Mac OS X 10.4, better known as Tiger, is faster than its predecessors, but nothing's too fast for Pogue and Mac OS X: The Missing Manual. There are many reasons why this is the most popular computer book of all time.With its hallmark objectivity, the Tiger Edition thoroughly explores the latest features to grace the Mac OS. Which ones work well and which do not? What should you look for? This book tackles Spotlight, an enhanced search feature that helps you find anything on your computer; iChat AV for videoconferencing; Automator for automating repetitive, manual or batch tasks; and the hundreds of smaller tweaks and changes, good and bad, that Apple's marketing never bothers to mention.Mac OS X: The Missing Manual, Tiger Edition is the authoritative book that's ideal for every user, including people coming to the Mac for the first time. Our guide offers an ideal introduction that demystifies the Dock, the unfamiliar Mac OS X folder structure, and the entirely new Mail application. There are also mini-manuals on iLife applications such as iMovie, iDVD, and iPhoto, those much-heralded digital media programs, and a tutorial for Safari, Mac's own web browser.And plenty more: learn to configure Mac OS X using the System Preferences application, keep your Mac secure with FileVault, and learn about Tiger's enhanced Firewall capabilities. If you're so inclined, this Missing Manual also offers an easy introduction to the Terminal application for issuing basic Unix commands.There's something new on practically every page, and David Pogue brings his celebrated wit and expertise to every one of them. Mac's brought a new cat to town and we have a great new way to tame it.

    But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

    Now delete that picture. In Once Upon an Algorithm, Martin Erwig explains computation as something that takes place beyond electronic computers, and computer science as the study of systematic problem solving. Erwig points out that many daily activities involve problem solving. Getting up in the morning, for example: You get up, take a shower, get dressed, eat breakfast. This simple daily routine solves a recurring problem through a series of well-defined steps. In computer science, such a routine is called an algorithm.Erwig illustrates a series of concepts in computing with examples from daily life and familiar stories. Hansel and Gretel, for example, execute an algorithm to get home from the forest. The movie Groundhog Day illustrates the problem of unsolvability; Sherlock Holmes manipulates data structures when solving a crime; the magic in Harry Potter's world is understood through types and abstraction; and Indiana Jones demonstrates the complexity of searching. Along the way, Erwig also discusses representations and different ways to organize data; "intractable" problems; language, syntax, and ambiguity; control structures, loops, and the halting problem; different forms of recursion; and rules for finding errors in algorithms.This engaging book explains computation accessibly and shows its relevance to daily life. Something to think about next time we execute the algorithm of getting up in the morning.

    Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs -- with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will:Solve a particular coding problem or improve on the performance of an existing solutionQuickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to useGet algorithmic solutions in C, C++, Java, and Ruby with implementation tipsLearn the expected performance of an algorithm, and the conditions it needs to perform at its bestDiscover the impact that similar design decisions have on different algorithmsLearn advanced data structures to improve the efficiency of algorithmsWith Algorithms in a Nutshell, you'll learn how to improve the performance of key algorithms essential for the success of your software applications.

    This is the first book that introduces Lisp as a language for the real world.Practical Common Lisp presents a thorough introduction to Common Lisp, providing you with an overall understanding of the language features and how they work. Over a third of the book is devoted to practical examples, such as the core of a spam filter and a web application for browsing MP3s and streaming them via the Shoutcast protocol to any standard MP3 client software (e.g., iTunes, XMMS, or WinAmp). In other "practical" chapters, author Peter Seibel demonstrates how to build a simple but flexible in-memory database, how to parse binary files, and how to build a unit test framework in 26 lines of code.

    We nevertheless muddle through even in the absence of theories of how to act. But how do we do it?In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own. The key is “probably approximately correct” algorithms, a concept Valiant developed to explain how effective behavior can be learned. The model shows that pragmatically coping with a problem can provide a satisfactory solution in the absence of any theory of the problem. After all, finding a mate does not require a theory of mating. Valiant’s theory reveals the shared computational nature of evolution and learning, and sheds light on perennial questions such as nature versus nurture and the limits of artificial intelligence.Offering a powerful and elegant model that encompasses life’s complexity, Probably Approximately Correct has profound implications for how we think about behavior, cognition, biological evolution, and the possibilities and limits of human and machine intelligence.

    It presents the mathematical foundations of computer graphics with a focus on geometric intuition, allowing the programmer to understand and apply those foundations to the development of efficient code. - The fundamental mathematics used in graphics programs - The basics of the graphics pipeline - BSP trees - Ray tracing - Surface shading - Texture mapping Advanced topics include: - Curves and surfaces - Color science - Global illumination - Reflection models - Image-based rendering - Visualization Extensive exercises and references for further reading enhance each chapter. An introduction for novices---a refresher for professionals.

    Today, our entire modern way of life, from communication to commerce to conflict, fundamentally depends on the Internet. And the cybersecurity issues that result challenge literally everyone: politicians wrestling with everything from cybercrime to online freedom; generals protecting the nation from new forms of attack, while planning new cyberwars; business executives defending firms from once unimaginable threats, and looking to make money off of them; lawyers and ethicists building new frameworks for right and wrong. Most of all, cybersecurity issues affect us as individuals. We face new questions in everything from our rights and responsibilities as citizens of both the online and real world to simply how to protect ourselves and our families from a new type of danger. And yet, there is perhaps no issue that has grown so important, so quickly, and that touches so many, that remains so poorly understood.In Cybersecurity and CyberWar: What Everyone Needs to Know�, New York Times best-selling author P. W. Singer and noted cyber expert Allan Friedman team up to provide the kind of easy-to-read, yet deeply informative resource book that has been missing on this crucial issue of 21st century life. Written in a lively, accessible style, filled with engaging stories and illustrative anecdotes, the book is structured around the key question areas of cyberspace and its security: how it all works, why it all matters, and what can we do? Along the way, they take readers on a tour of the important (and entertaining) issues and characters of cybersecurity, from the "Anonymous" hacker group and the Stuxnet computer virus to the new cyber units of the Chinese and U.S. militaries. Cybersecurity and CyberWar: What Everyone Needs to Know� is the definitive account on the subject for us all, which comes not a moment too soon.What Everyone Needs to Know� is a registered trademark of Oxford University Press.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    The book focuses on techniques of lasting value and explains them precisely in terms of a simple abstract machine. The book presents all major programming paradigms in a uniform framework that shows their deep relationships and how and where to use them together.After an introduction to programming concepts, the book presents both well-known and lesser-known computation models ("programming paradigms"). Each model has its own set of techniques and each is included on the basis of its usefulness in practice. The general models include declarative programming, declarative concurrency, message-passing concurrency, explicit state, object-oriented programming, shared-state concurrency, and relational programming. Specialized models include graphical user interface programming, distributed programming, and constraint programming. Each model is based on its kernel language—a simple core language that consists of a small number of programmer- significant elements. The kernel languages are introduced progressively, adding concepts one by one, thus showing the deep relationships between different models. The kernel languages are defined precisely in terms of a simple abstract machine. Because a wide variety of languages and programming paradigms can be modeled by a small set of closely related kernel languages, this approach allows programmer and student to grasp the underlying unity of programming. The book has many program fragments and exercises, all of which can be run on the Mozart Programming System, an Open Source software package that features an interactive incremental development environment.

    Albert-László Barabási, the nation’s foremost expert in the new science of networks and author of Bursts, takes us on an intellectual adventure to prove that social networks, corporations, and living organisms are more similar than previously thought. Grasping a full understanding of network science will someday allow us to design blue-chip businesses, stop the outbreak of deadly diseases, and influence the exchange of ideas and information. Just as James Gleick and the Erdos–Rényi model brought the discovery of chaos theory to the general public, Linked tells the story of the true science of the future and of experiments in statistical mechanics on the internet, all vital parts of what would eventually be called the Barabási–Albert model.

    

    From Stephen Levy—the author who made "hackers" a household word—comes this account of a revolution that is already affecting every citizen in the twenty-first century. Crypto tells the inside story of how a group of "crypto rebels"—nerds and visionaries turned freedom fighters—teamed up with corporate interests to beat Big Brother and ensure our privacy on the Internet. Levy's history of one of the most controversial and important topics of the digital age reads like the best futuristic fiction.