Understanding Computation explains theoretical computer science in a context you’ll recognize, helping you appreciate why these ideas matter and how they can inform your day-to-day programming.Rather than use mathematical notation or an unfamiliar academic programming language like Haskell or Lisp, this book uses Ruby in a reductionist manner to present formal semantics, automata theory, and functional programming with the lambda calculus. It’s ideal for programmers versed in modern languages, with little or no formal training in computer science.* Understand fundamental computing concepts, such as Turing completeness in languages* Discover how programs use dynamic semantics to communicate ideas to machines* Explore what a computer can do when reduced to its bare essentials* Learn how universal Turing machines led to today’s general-purpose computers* Perform complex calculations, using simple languages and cellular automata* Determine which programming language features are essential for computation* Examine how halting and self-referencing make some computing problems unsolvable* Analyze programs by using abstract interpretation and type systems

    By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.

    "An immensely fun and -- one cannot emphasize this enough -- accessible history of the first outlaws in cyberspace."--Glamour

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

    This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

    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 cause of their failure was a complete mystery.Five months later, a seemingly unrelated event occurred. A computer security firm in Belarus was called in to troubleshoot some computers in Iran that were caught in a reboot loop—crashing and rebooting repeatedly. At first, technicians with the firm believed the malicious code they found on the machines was a simple, routine piece of malware. But as they and other experts around the world investigated, they discovered a virus of unparalleled complexity and mysterious provenance and intent. They had, they soon learned, stumbled upon the world’s first digital weapon.Stuxnet, as it came to be known, was unlike any other virus or worm built before: It was the first attack that reached beyond the computers it targeted to physically destroy the equipment those computers controlled. It was an ingenious attack, jointly engineered by the United States and Israel, that worked exactly as planned, until the rebooting machines gave it all away. And the discovery of Stuxnet was just the beginning: Once the digital weapon was uncovered and deciphered, it provided clues to other tools lurking in the wild. Soon, security experts found and exposed not one but three highly sophisticated digital spy tools that came from the same labs that created Stuxnet. The discoveries gave the world its first look at the scope and sophistication of nation-state surveillance and warfare in the digital age.Kim Zetter, a senior reporter at Wired, has covered hackers and computer security since 1999 and is one of the top journalists in the world on this beat. She was among the first reporters to cover Stuxnet after its discovery and has authored many of the most comprehensive articles about it. In COUNTDOWN TO ZERO DAY: Stuxnet and the Launch of the World’s First Digital Weapon, Zetter expands on this work to show how the code was designed and unleashed and how its use opened a Pandora’s Box, ushering in an age of digital warfare in which any country’s infrastructure—power grids, nuclear plants, oil pipelines, dams—is vulnerable to the same kind of attack with potentially devastating results. A sophisticated digital strike on portions of the power grid, for example, could plunge half the U.S. into darkness for weeks or longer, having a domino effect on all other critical infrastructures dependent on electricity.

    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.""

    Old-fashioned entrepreneurship combined with scientific know-how inspired now famous computer engineers to create the technology that became IBM. Wartime needs drove the giant ENIAC, the first fully electronic computer. Later, the PC enabled modes of computing that liberated people from room-sized, mainframe computers. This second edition now extends beyond the development of Microsoft Windows and the Internet, to include open source operating systems like Linux, and the rise again and fall and potential rise of the dot.com industries.

    The Atari VCS was affordable and offered the flexibility of changeable cartridges. Nearly a thousand of these were created, the most significant of which established new techniques, mechanics, and even entire genres. This book offers a detailed and accessible study of this influential video game console from both computational and cultural perspectives.Studies of digital media have rarely investigated platforms--the systems underlying computing. This book (the first in a series of Platform Studies) does so, developing a critical approach that examines the relationship between platforms and creative expression. Nick Montfort and Ian Bogost discuss the Atari VCS itself and examine in detail six game cartridges: Combat, Adventure, Pac-Man, Yars' Revenge, Pitfall!, and Star Wars: The Empire Strikes Back. They describe the technical constraints and affordances of the system and track developments in programming, gameplay, interface, and aesthetics. Adventure, for example, was the first game to represent a virtual space larger than the screen (anticipating the boundless virtual spaces of such later games as World of Warcraft and Grand Theft Auto), by allowing the player to walk off one side into another space; and Star Wars: The Empire Strikes Back was an early instance of interaction between media properties and video games. Montfort and Bogost show that the Atari VCS--often considered merely a retro fetish object--is an essential part of the history of video games.

    After a year of self-study, I learned to program well enough to land a job as a software engineer II at eBay. Once I got there, I realized I was severely under-prepared. I was overwhelmed by the amount of things I needed to know but hadn't learned yet. My journey learning to program, and my experience at my first job as a software engineer were the inspiration for this book. This book is not just about learning to program; although you will learn to code. If you want to program professionally, it is not enough to learn to code; that is why, in addition to helping you learn to program, I also cover the rest of the things you need to know to program professionally that classes and books don't teach you. "The Self-taught Programmer" is a roadmap, a guide to take you from writing your first Python program, to passing your first technical interview. I divided the book into five sections: 1. Start to program in Python 3 and build your first program.2. Learn Object-oriented programming and create a powerful Python program to get you hooked.3. Learn to use tools like Git, Bash, and regular expressions. Then use your new coding skills to build a web scraper.4. Study Computer Science fundamentals like data structures and algorithms.5. Finish with best coding practices, tips for working with a team, and advice on landing a programming job.You CAN learn to program professionally. The path is there. Will you take it?

    Chairman and co-founder of Microsoft, Bill Gates is the most powerful person in the computer industry and the youngest self-made billionaire in history. His company's DOS and Windows programs are such universal standards that more than nine out of ten personal computers depend on Microsoft software. Under the "Microsoft Everywhere" rallying cry, Gates intends to expand his company's worldwide dominance to office equipment, communications, and home entertainment. Vivid and definitive, Gates details the behind the scenes history of the personal computer industry and its movers and shakers, from Apple to IBM, from Steve Jobs to Ross Perot. Uncovering the inside stories of the bitter battle for control of the expanding personal computing market, Gates is a bracing, comprehensive portrait of the industry, the company, and the man-- and what they mean for a future where software is everything.

    Topics covered include:Basic version control commands and conceptsIntroduction to Distributed Version Control Systems (DVCS)Advanced branching workflowsStrengths and weaknesses of DVCS vs. centralized toolsBest practicesHow distributed version control works under the hoodFeaturing these open source version control tools:Apache SubversionMercurialGitVeracity

    Johnson. It was the first book exclusively on the theory of NP-completeness and computational intractability. The book features an appendix providing a thorough compendium of NP-complete problems (which was updated in later printings of the book). The book is now outdated in some respects as it does not cover more recent development such as the PCP theorem. It is nevertheless still in print and is regarded as a classic: in a 2006 study, the CiteSeer search engine listed the book as the most cited reference in computer science literature.

    He found this in Jim Clark, a man whose achievements include the founding of three separate billion-dollar companies. Lewis also found much more, and the result—the best-selling book The New New Thing—is an ingeniously conceived history of the Internet revolution.