The book begins by introducing the unique features and concepts of Go. Then, you'll get hands-on experience writing real-world applications including websites and network servers, as well as techniques to manipulate and convert data at speeds that will make your friends jealous.

    Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.

    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?

    It’s time we stand face-to-digital-face with the true powers and limitations of the algorithms that already automate important decisions in healthcare, transportation, crime, and commerce. Hello World is indispensable preparation for the moral quandaries of a world run by code, and with the unfailingly entertaining Hannah Fry as our guide, we’ll be discussing these issues long after the last page is turned.

    Like many others, I feel like I have learned more in the last couple of years studying Bitcoin than I have during two decades of formal education. The following lessons are a distillation of what I’ve learned. First published as an article series titled “What I’ve Learned From Bitcoin,” what follows can be seen as a third edition of the original series. Like Bitcoin, these lessons aren’t a static thing. I plan to work on them periodically, releasing updated versions and additional material in the future.Bitcoin is an inexhaustible teacher, which is why I do not claim that these lessons are all-encompassing or complete. They are a reflection of my personal journey down the rabbit hole. There are many more lessons to be learned, and every person will learn something different from entering the world of Bitcoin. I hope that you will find these lessons useful and that the process of learning them by reading won’t be as arduous and painful as learning them firsthand.

    No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    You'll learn how to write web services from scratch and integrate existing services into your Java applications. With Java Web Services: Up and Running, you will:Understand the distinction between SOAP-based and REST-style services Write, deploy, and consume SOAP-based services in core Java Understand the Web Service Definition Language (WSDL) service contract Recognize the structure of a SOAP message Learn how to deliver Java-based RESTful web services and consume commercial RESTful services Know security requirements for SOAP- and REST-based web services Learn how to implement JAX-WS in various application servers Ideal for students as well as experienced programmers, Java Web Services: Up and Running is the concise guide you need to start working with these technologies right away.

    The most common operation done with sed is substitution, replacing one block of text with another. awk is a complete programming language. Unlike many conventional languages, awk is "data driven" -- you specify what kind of data you are interested in and the operations to be performed when that data is found. awk does many things for you, including automatically opening and closing data files, reading records, breaking the records up into fields, and counting the records. While awk provides the features of most conventional programming languages, it also includes some unconventional features, such as extended regular expression matching and associative arrays. sed & awk describes both programs in detail and includes a chapter of example sed and awk scripts. This edition covers features of sed and awk that are mandated by the POSIX standard. This most notably affects awk, where POSIX standardized a new variable, CONVFMT, and new functions, toupper() and tolower(). The CONVFMT variable specifies the conversion format to use when converting numbers to strings (awk used to use OFMT for this purpose). The toupper() and tolower() functions each take a (presumably mixed case) string argument and return a new version of the string with all letters translated to the corresponding case. In addition, this edition covers GNU sed, newly available since the first edition. It also updates the first edition coverage of Bell Labs nawk and GNU awk (gawk), covers mawk, an additional freely available implementation of awk, and briefly discusses three commercial versions of awk, MKS awk, Thompson Automation awk (tawk), and Videosoft (VSAwk).

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    because the language seems like a good way to accomplish programming tasks that don't require the low-level bit handling power of C.-- Richard Bejtlich, TaoSecurityPython is a new and innovative scripting language. It is set to replace Perl as the programming language of choice for shell scripters, and for serious application developers who want a feature-rich, yet simple language to deploy their products.Dive Into Python is a hands-on guide to the Python language. Each chapter starts with a real, complete code sample, proceeds to pick it apart and explain the pieces, and then puts it all back together in a summary at the end.This is the perfect resource for you if you like to jump into languages fast and get going right away. If you're just starting to learn Python, first pick up a copy of Magnus Lie Hetland's Practical Python.

    It could forever change how you experience and interact with your physical surroundings, open your eyes to the perversity of bad design and the desirability of good design, and raise your expectations about how things should be designed.B & W photographs and illustrations throughout.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    The book teaches a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.

    Quite the contrary; mistakes are easy to make and can often fully compromise security. Bulletproof SSL and TLS is the first SSL book written with users in mind. It is the book you will want to read if you need to assess risks related to website encryption, manage keys and certificates, configure secure servers, and deploy secure web applications. Bulletproof SSL and TLS is based on several years of work researching SSL and how SSL is used in real life, implementing and supporting a comprehensive assessment tool running on the SSL Labs website (https://www.ssllabs.com), and assessing most of the public SSL servers on the Internet. The assessment tool helped many site owners identify and solve issues with their SSL deployments. The intent of this book is to provide a definitive reference for SSL deployment that is full of practical and relevant information.