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.

    In How the Internet Happened, he chronicles the whole fascinating story for the first time, beginning in a dusty Illinois basement in 1993, when a group of college kids set off a once-in-an-epoch revolution with what would become the first “dotcom.”Depicting the lives of now-famous innovators like Netscape’s Marc Andreessen and Facebook’s Mark Zuckerberg, McCullough also reveals surprising quirks and unknown tales as he tracks both the technology and the culture around the internet’s rise. Cinematic in detail and unprecedented in scope, the result both enlightens and informs as it draws back the curtain on the new rhythm of disruption and innovation the internet fostered, and helps to redefine an era that changed every part of our lives.

    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.""

     For decades, technology encouraged people to squander their time and intellect as passive consumers. Today, tech has finally caught up with human potential. In Cognitive Surplus, Internet guru Clay Shirky forecasts the thrilling changes we will all enjoy as new digital technology puts our untapped resources of talent and goodwill to use at last. Since we Americans were suburbanized and educated by the postwar boom, we've had a surfeit of intellect, energy, and time-what Shirky calls a cognitive surplus. But this abundance had little impact on the common good because television consumed the lion's share of it-and we consume TV passively, in isolation from one another. Now, for the first time, people are embracing new media that allow us to pool our efforts at vanishingly low cost. The results of this aggregated effort range from mind expanding-reference tools like Wikipedia-to lifesaving-such as Ushahidi.com, which has allowed Kenyans to sidestep government censorship and report on acts of violence in real time. Shirky argues persuasively that this cognitive surplus-rather than being some strange new departure from normal behavior-actually returns our society to forms of collaboration that were natural to us up through the early twentieth century. He also charts the vast effects that our cognitive surplus- aided by new technologies-will have on twenty-first-century society, and how we can best exploit those effects. Shirky envisions an era of lower creative quality on average but greater innovation, an increase in transparency in all areas of society, and a dramatic rise in productivity that will transform our civilization. The potential impact of cognitive surplus is enormous. As Shirky points out, Wikipedia was built out of roughly 1 percent of the man-hours that Americans spend watching TV every year. Wikipedia and other current products of cognitive surplus are only the iceberg's tip. Shirky shows how society and our daily lives will be improved dramatically as we learn to exploit our goodwill and free time like never before.

    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.

    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

    Negroponte's fans will want to get a copy of Being Digital, which is an edited version of the 18 articles he wrote for Wired about "being digital." Negroponte's text is mostly a history of media technology rather than a set of predictions for future technologies. In the beginning, he describes the evolution of CD-ROMs, multimedia, hypermedia, HDTV (high-definition television), and more. The section on interfaces is informative, offering an up-to-date history on visual interfaces, graphics, virtual reality (VR), holograms, teleconferencing hardware, the mouse and touch-sensitive interfaces, and speech recognition. In the last chapter and the epilogue, Negroponte offers visionary insight on what "being digital" means for our future. Negroponte praises computers for their educational value but recognizes certain dangers of technological advances, such as increased software and data piracy and huge shifts in our job market that will require workers to transfer their skills to the digital medium. Overall, Being Digital provides an informative history of the rise of technology and some interesting predictions for its future.

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    He needed a way to keep track of software development over time – whatever he was thinking about or working on. He researched subjects he found interesting, then documented his research with a public blog post, which he could easily find and refer to later. Over time, increasing numbers of blog visitors found the posts helpful, relevant and interesting. Now, approximately 100,000 readers visit the blog per day and nearly as many comment and interact on the site.Effective Programming: More Than Writing Code is your one-stop shop for all things programming. Jeff writes with humor and understanding, allowing for both seasoned programmers and newbies to appreciate the depth of his research. From such posts as“The Programmer’s Bill of Rights” and “Why Cant Programmers... Program?” to “Working With the Chaos Monkey,” this book introduces the importance of writing responsible code, the logistics involved, and how people should view it more as a lifestyle than a career.

    As they helped grow Google from a young start-up to a global icon, they relearned everything they knew about management. How Google Works is the sum of those experiences distilled into a fun, easy-to-read primer on corporate culture, strategy, talent, decision-making, communication, innovation, and dealing with disruption.The authors explain how the confluence of three seismic changes - the internet, mobile, and cloud computing - has shifted the balance of power from companies to consumers. The companies that will thrive in this ever-changing landscape will be the ones that create superior products and attract a new breed of multifaceted employees whom the authors dub 'smart creatives'. The management maxims ('Consensus requires dissension', 'Exile knaves but fight for divas', 'Think 10X, not 10%') are illustrated with previously unreported anecdotes from Google's corporate history.'Back in 2010, Eric and I created an internal class for Google managers,' says Rosenberg. 'The class slides all read 'Google confidential' until an employee suggested we uphold the spirit of openness and share them with the world. This book codifies the recipe for our secret sauce: how Google innovates and how it empowers employees to succeed.'

    Often, computer science and computer engineering curricula don't provide students with a concentrated and consistent introduction to the fundamental concepts that underlie all computer systems. Traditional computer organization and logic design courses cover some of this material, but they focus largely on hardware design. They provide students with little or no understanding of how important software components operate, how application programs use systems, or how system attributes affect the performance and correctness of application programs. - A more complete view of systems - Takes a broader view of systems than traditional computer organization books, covering aspects of computer design, operating systems, compilers, and networking, provides students with the understanding of how programs run on real systems. - Systems presented from a programmers perspective - Material is presented in such a way that it has clear benefit to application programmers, students learn how to use this knowledge to improve program performance and reliability. They also become more effective in program debugging, because t

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    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

    ―Jacob Boudreau CTO of Stord | Forbes 30 Under 30 Joel's book and show provide incredible insights for young startup developers and fellow CTOs alike. Joel offers a human perspective and real practical advice on the challenges and opportunities facing every Modern CTO. ― Christian Saucier | Entrepreneur and P2P Systems Architect I've really come to respect what Joel is doing in the community. His podcast and book are filling a much needed hole and I'm excited to see what else the future has in store. ― Don Pawlowski Chief Technology Officer at University Tees Modern CTO Everything you need to know to be a Modern CTO. Developers are not CTOs, but developers can learn how to be CTOs. In Modern CTO, Joel Beasley provides readers with an in-depth road map on how to successfully navigate the unexplored and jagged transition between these two roles. Drawing from personal experience, Joel gives a refreshing take on the challenges, lessons, and things to avoid on this journey.Readers will learn how Modern CTOs: Manage deadlines Speak up Know when to abandon ship and build a better one Deal with poor code Avoid getting lost in the product and know what UX mistakes to watch out for Manage people and create momentum … plus much more Modern CTO is the ultimate book when making the leap from developer to CTO. Update: Kindle Formatting issues resolved 5/13/18. Thank you for the feedback.

    The authors present updated coverage of compilers based on research and techniques that have been developed in the field over the past few years. The book provides a thorough introduction to compiler design and covers topics such as context-free grammars, fine state machines, and syntax-directed translation.