In 1985, a new version of the language was developed, incorporating additional features such as multiple input files, dynamic regular expressions, and user-defined functions. This new version is available for both Unix and MS-DOS. This is the first book on AWK. It begins with a tutorial that shows how easy AWK is to use. The tutorial is followed by a comprehensive manual for the new version of AWK. Subsequent chapters illustrate the language by a range of useful applications, such as: Retrieving, transforming, reducing, and validating data Managing small, personal databases Text processing Little languages Experimenting with algorithms The examples illustrates the books three themes: showing how to use AWK well, demonstrating AWKs versatility, and explaining how common computing operations are done. In addition, the book contains two appendixes: summary of the language, and answers to selected exercises.

    Where do you begin? Head First iPhone Development will help you get your first application up and running in no time. You'll quickly learn to use iPhone SDK tools, including Interface Builder and Xcode, and master Objective-C programming principles that will make your app stand out. It's a complete learning experience for creating eye-catching, top-selling iPhone applications.Put Objective-C core concepts to work, including message passing, protocols, properties, and memory managementTake advantage of iPhone patterns such as datasources and delegatesPreview your applications in the iPhone SimulatorBuild complicated interactions that utilize multiple views, data entry/editing, and iPhone rotationWork with iPhone's camera, GPS, and accelerometerOptimize, test, and distribute your applicationWe think your time is too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First iPhone Development provides a visually-rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

    Today, Intel and other semiconductor firms are abandoning the single fast processor model in favor of multi-core microprocessors--chips that combine two or more processors in a single package. In the fourth edition of "Computer Architecture," the authors focus on this historic shift, increasing their coverage of multiprocessors and exploring the most effective ways of achieving parallelism as the key to unlocking the power of multiple processor architectures. Additionally, the new edition has expanded and updated coverage of design topics beyond processor performance, including power, reliability, availability, and dependability. CD System Requirements"PDF Viewer"The CD material includes PDF documents that you can read with a PDF viewer such as Adobe, Acrobat or Adobe Reader. Recent versions of Adobe Reader for some platforms are included on the CD. "HTML Browser"The navigation framework on this CD is delivered in HTML and JavaScript. It is recommended that you install the latest version of your favorite HTML browser to view this CD. The content has been verified under Windows XP with the following browsers: Internet Explorer 6.0, Firefox 1.5; under Mac OS X (Panther) with the following browsers: Internet Explorer 5.2, Firefox 1.0.6, Safari 1.3; and under Mandriva Linux 2006 with the following browsers: Firefox 1.0.6, Konqueror 3.4.2, Mozilla 1.7.11. The content is designed to be viewed in a browser window that is at least 720 pixels wide. You may find the content does not display well if your display is not set to at least 1024x768 pixel resolution. "Operating System"This CD can be used under any operating system that includes an HTML browser and a PDF viewer. This includes Windows, Mac OS, and most Linux and Unix systems. Increased coverage on achieving parallelism with multiprocessors. Case studies of latest technology from industry including the Sun Niagara Multiprocessor, AMD Opteron, and Pentium 4. Three review appendices, included in the printed volume, review the basic and intermediate principles the main text relies upon. Eight reference appendices, collected on the CD, cover a range of topics including specific architectures, embedded systems, application specific processors--some guest authored by subject experts.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    Starting with basic examples, this book is focused solely on Java 8 language changes and related API changes, so you don’t need to buy and read a 900 page book in order to brush up. Lambdas make a programmer's job easier, and this book will teach you how. Coverage includes introductory syntax for lambda expressions, method references that allow you to reuse existing named methods from your codebase, and the collection library in Java 8.

    Jonathan Stark shows you how to leverage your existing web development skills to build native iPhone applications using these technologies." --John Allsopp, author and founder of Web Directions"Jonathan's book is the most comprehensive documentation available for developing web applications for mobile Safari. Not just great tech coverage, this book is an easy read of purely fascinating mobile tidbits in a fun colloquial style. Must have for all PhoneGap developers." -- Brian LeRoux, Nitobi SoftwareIt's a fact: if you know HTML, CSS, and JavaScript, you already have the tools you need to develop your own iPhone apps. With this book, you'll learn how to use these open source web technologies to design and build apps for the iPhone and iPod Touch on the platform of your choice-without using Objective-C or Cocoa.Device-agnostic mobile apps are the wave of the future, and this book shows you how to create one product for several platforms. You'll find guidelines for converting your product into a native iPhone app using the free PhoneGap framework. And you'll learn why releasing your product as a web app first helps you find, fix, and test bugs much faster than if you went straight to the App Store with a product built with Apple's tools.Build iPhone apps with tools you already know how to useLearn how to make an existing website look and behave like an iPhone appAdd native-looking animations to your web app using jQTouchTake advantage of client-side data storage with apps that run even when the iPhone is offlineHook into advanced iPhone features -- including the accelerometer, geolocation, and vibration -- with JavaScriptSubmit your applications to the App Store with XcodeThis book received valuable community input through O'Reilly's Open Feedback Publishing System (OFPS). Learn more at http://labs.oreilly.com/ofps.html.

    Whether you're building the next killer app, investing in a startup, or simply curious about the technology, this practical book is essential reading.Bitcoin, the first successful decentralized digital currency, is still in its infancy and it's already spawned a multi-billion dollar global economy. This economy is open to anyone with the knowledge and passion to participate. Mastering Bitcoin provides you with the knowledge you need (passion not included).This book includes:A broad introduction to bitcoin--ideal for non-technical users, investors, and business executivesAn explanation of the technical foundations of bitcoin and cryptographic currencies for developers, engineers, and software and systems architectsDetails of the bitcoin decentralized network, peer-to-peer architecture, transaction lifecycle, and security principlesOffshoots of the bitcoin and blockchain inventions, including alternative chains, currencies, and applicationsUser stories, analogies, examples, and code snippets illustrating key technical concepts

    Python is easy to learn, and it's perfect for exploring topics like statistics, geometry, probability, and calculus. You’ll learn to write programs to find derivatives, solve equations graphically, manipulate algebraic expressions, even examine projectile motion.Rather than crank through tedious calculations by hand, you'll learn how to use Python functions and modules to handle the number crunching while you focus on the principles behind the math. Exercises throughout teach fundamental programming concepts, like using functions, handling user input, and reading and manipulating data. As you learn to think computationally, you'll discover new ways to explore and think about math, and gain valuable programming skills that you can use to continue your study of math and computer science.If you’re interested in math but have yet to dip into programming, you’ll find that Python makes it easy to go deeper into the subject—let Python handle the tedious work while you spend more time on the math.

    Spring Boot and Spring Cloud offer Java developers an easy migration path from traditional monolithic Spring applications to microservice-based applications that can be deployed to multiple cloud platforms. The Spring Boot and Spring Cloud frameworks let you quickly build microservices that are ready to be deployed to a private corporate cloud or a public cloud like Amazon Web Services (AWS) or Pivotal’s CloudFoundry.Spring Microservices in Action teaches you how to use the Spring Boot and Spring Cloud frameworks to build and deploy microservice-based cloud applications. You'll begin with an introduction to the microservice pattern and how to build microservices with Spring Boot and Spring Cloud. Then you'll get hands-on and discover how to configure Spring Boot. Using lots of real-world examples, you'll learn topics like service discovery with Spring Cloud, Netflix Eureka, and Ribbon. Next, you'll find out how to handle potential problems using client-side resiliency patterns with Spring and Netflix Hystrix. This book also covers implementing a service gateway with Spring Cloud and Zuul and event processing in the cloud with Spring Cloud Stream. Finally, you'll learn to deploy and push your application to cloud services, including AWS and CloudFoundry. By the end of this book, you'll not only be able to build your own microservice-based applications, but how operationalize and scale your microservices so they can deployed to a private or public cloud.

    It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. We cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

    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.

    These tools help programmers build compilers and interpreters, but they also have a wider range of applications.The second edition contains completely revised tutorial sections for novice users and reference sections for advanced users. This edition is twice the size of the first and has an expanded index.The following material has been added:Each utility is explained in a chapter that covers basic usage and simple, stand-alone applications How to implement a full SQL grammar, with full sample code Major MS-DOS and Unix versions of lex and yacc are explored in depth, including AT&T lex and yacc, Berkeley yacc, Berkeley/GNU Flex, GNU Bison, MKS lex and yacc, and Abraxas PCYACC

    The Mikado Method is a process for surfacing the dependencies in a codebase, so that you can systematically eliminate technical debt and get things done.It gets its name from a simple game commonly known as "pick-up sticks." You start with a jumbled pile of sticks. The goal is to remove the Mikado, or Emperor, stick without disturbing the others. Players carefully remove sticks one at a time, leaving the rest of the heap intact, slowly exposing the Mikado. The game is a great metaphor for eliminating technical debt—carefully extracting each intertwined dependency until you're able to successfully resolve the central issue and move on.The Mikado Method is a book by the creators of this process. It describes a pragmatic, straightforward, and empirical method to plan and perform non-trivial technical improvements on an existing software system. The method has simple rules, but the applicability is vast. As you read, you'll practice a step-by-step system for identifying the scope and nature of your technical debt, mapping the key dependencies, and determining the safest way to approach the "Mikado"-your goal. A natural byproduct of this process is the Mikado Graph, a minimalistic, relevant, just-in-time roadmap and information radiator that reflects deep understanding of how your system works.

    We'll introduce you to various tips, tricks, patterns, code snippets, and techniques that we've picked up over the years.This book is great for:Beginners who have just finished the Django tutorial.Developers with intermediate knowledge of Django who want to improve their Django projects.

    I'm going to share that mindset with you — along with hundreds of actionable techniques and proven habits — so you can shortcut those years.Introducing The Effective Engineer — the only book designed specifically for today's software engineers, based on extensive interviews with engineering leaders at top tech companies, and packed with hundreds of techniques to accelerate your career.For two years, I embarked on a quest seeking an answer to one question:How do the most effective engineers make their efforts, their teams, and their careers more successful?I interviewed and collected stories from engineering VPs, directors, managers, and other leaders at today's top software companies: established, household names like Google, Facebook, Twitter, and LinkedIn; rapidly growing mid-sized companies like Dropbox, Square, Box, Airbnb, and Etsy; and startups like Reddit, Stripe, Instagram, and Lyft.These leaders shared stories about the most valuable insights they've learned and the most common and costly mistakes that they've seen engineers — sometimes themselves — make.This is just a small sampling of the hard questions I posed to them:- What engineering qualities correlate with future success?- What have you done that has paid off the highest returns?- What separates the most effective engineers you've worked with from everyone else?- What's the most valuable lesson your team has learned in the past year?- What advice do you give to new engineers on your team? Everyone's story is different, but many of the lessons share common themes.You'll get to hear stories like:- How did Instagram's team of 5 engineers build and support a service that grew to over 40 million users by the time the company was acquired?- How and why did Quora deploy code to production 40 to 50 times per day?- How did the team behind Google Docs become the fastest acquisition to rewrite its software to run on Google's infrastructure?- How does Etsy use continuous experimentation to design features that are guaranteed to increase revenue at launch?- How did Facebook's small infrastructure team effectively operate thousands of database servers?- How did Dropbox go from barely hiring any new engineers to nearly tripling its team size year-over-year? What's more, I've distilled their stories into actionable habits and lessons that you can follow step-by-step to make your career and your team more successful.The skills used by effective engineers are all learnable.And I'll teach them to you. With The Effective Engineer, I'll teach you a unifying framework called leverage — the value produced per unit of time invested — that you can use to identify the activities that produce disproportionate results.Here's a sneak peek at some of the lessons you'll learn. You'll learn how to:- Prioritize the right projects and tasks to increase your impact.- Earn more leeway from your peers and managers on your projects.- Spend less time maintaining and fixing software and more time building and shipping new features.- Produce more accurate software estimates.- Validate your ideas cheaply to reduce wasted work.- Navigate organizational and people-related bottlenecks.- Find the appropriate level of code reviews, testing, abstraction, and technical debt to balance speed and quality.- Shorten your debugging workflow to increase your iteration speed.