This handy reference will help project managers and students enhance their knowledge in specific areas and test themselves on issues that are essential to successful project management.

    The text is rounded off by rich, relevant, and teachable cases. This text's accessible writing style and wealth of new and updated illustrations, which clarify the most difficult topics, make this text the best resource for your students. The new case selections emphasize variety, currency, and familiar company names. The cases are up-to-date in terms of both financial data and strategic issues. This group of cases gives both instructors and students unparalleled quality and variety. Based on consistent reviewer feedback, these selections combine comprehensive and shorter length cases about well known companies.

     Rails(TM) AntiPatterns identifies these widespread Rails code and design problems, explains why they're bad and why they happen--and shows exactly what to do instead.The book is organized into concise, modular chapters--each outlines a single common AntiPattern and offers detailed, cookbook-style code solutions that were previously difficult or impossible to find. Leading Rails developers Chad Pytel and Tammer Saleh also offer specific guidance for refactoring existing bad code or design to reflect sound object-oriented principles and established Rails best practices. With their help, developers, architects, and testers can dramatically improve new and existing applications, avoid future problems, and establish superior Rails coding standards throughout their organizations.This book will help you understand, avoid, and solve problems withModel layer code, from general object-oriented programming violations to complex SQL and excessive redundancy Domain modeling, including schema and database issues such as normalization and serialization View layer tools and conventions Controller-layer code, including RESTful code Service-related APIs, including timeouts, exceptions, backgrounding, and response codes Third-party code, including plug-ins and gems Testing, from test suites to test-driven development processes Scaling and deployment Database issues, including migrations and validations System design for "graceful degradation" in the real world

    You'll read about humans who are invisible to computers, how a default password once caused a zombie apocalypse and why airlines sometimes give away free tickets. This is also a book on how to prevent, avoid and reduce the impact of such problems. Our lives are increasingly tracked, monitored and categorised by software, driving a flood of information into the vast sea of big data. In this brave new world, humans can't cope with information overload. Governments and companies alike rely on computers to automatically detect fraud, predict behaviour and enforce laws. Inflexible automatons, barely smarter than a fridge, now make life-changing decisions. Clever marketing tricks us into believing that phones, TV sets and even cars are somehow smart. Yet all those computer systems were created by people - people who are well-meaning but fallible and biased, clever but forgetful, and who have grand plans but are pressed for time. Digitising a piece of work doesn't mean there will be no mistakes, but instead guarantees that when mistakes happen, they'll run at a massive scale. The next time you bang your head against a digital wall, the stories in this book will help you understand better what's going on and show you where to look for problems. If nothing else, when it seems as if you're under a black-magic spell, these stories will at least allow you to see the lighter side of the binary chaos. For people involved in software delivery, this book will help you find more empathy for people suffering from our mistakes, and discover heuristics to use during analysis, development or testing to make your software less error prone. <

    This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

    Programmers, developers, and engineers need to understand the underlying principles and paradigms as well as the real-world application of those principles. Now, internationally renowned expert Andrew S. Tanenbaum – with colleague Martin van Steen – presents a complete introduction that identifies the seven key principles of distributed systems, with extensive examples of each.Adds a completely new chapter on architecture to address the principle of organizing distributed systems. Provides extensive new material on peer-to-peer systems, grid computing and Web services, virtualization, and application-level multicasting. Updates material on clock synchronization, data-centric consistency, object-based distributed systems, and file systems and Web systems coordination.For all developers, software engineers, and architects who need an in-depth understanding of distributed systems.

    Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience.

    The book will teach you about:* Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data* Deep learning, a powerful set of techniques for learning in neural networksNeural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.

    They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.

    This concise book presents a set of API design rules, drawn primarily from best practices that stick close to the Web’s REST architectural style. Along with rules for URI design and HTTP use, you’ll learn guidelines for media types and representational forms. REST APIs are ubiquitous, but few of them follow a consistent design methodology. Using these simple rules, you will design web service APIs that adhere to recognized web standards. To assist you, author Mark Massé introduces the Web Resource Modeling Language (WRML), a conceptual framework he created for the design and implementation of REST APIs. Learn design rules for addressing resources with URIs Apply design principles to HTTP’s request methods and response status codes Work with guidelines for conveying metadata through HTTP headers and media types Get design tips to address the needs of client programs, including the special needs of browser-based JavaScript clients Understand why REST APIs should be designed and configured, not coded

    This classic book uncovers what interviews are really like at America's top software and computer companies and provides you with the tools to succeed in any situation. The authors take you step-by-step through new problems and complex brainteasers they were asked during recent technical interviews. 50 interview scenarios are presented along with in-depth analysis of the possible solutions. The problem-solving process is clearly illustrated so you'll be able to easily apply what you've learned during crunch time. You'll also find expert tips on what questions to ask, how to approach a problem, and how to recover if you become stuck. All of this will help you ace the interview and get the job you want.What you will learn from this bookTips for effectively completing the job application Ways to prepare for the entire programming interview process How to find the kind of programming job that fits you best Strategies for choosing a solution and what your approach says about you How to improve your interviewing skills so that you can respond to any question or situation Techniques for solving knowledge-based problems, logic puzzles, and programming problems Who this book is for This book is for programmers and developers applying for jobs in the software industry or in IT departments of major corporations.Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that will guide you through all the techniques involved.

    This book/CD-ROM package has now been updated to cover the latest version of the CCNA exam.

    Mastering this art will not only make you the most desired developer in the market, but it will transform the craziest deadline into "Consider it done, Sir".

    - Build an Angular 2 application from scratch using TypeScript and the Angular command line interface. - Write code using the paradigm of reactive programming with RxJS and Observables. - Know how to Unit Test Angular 2 using Jasmine, Karma and the Angular Test Bed The first chapter in the course is a quickstart where you dive straight into writing your first Angular 2 application. We use the web editor plunker so you can get stuck in writing code ASAP. In this quickstart you'll get a 50,000 foot view of the major features of Angular 2. Then chapter by chapter we go much deeper into each of these features. I'll cover the theory for that feature, using plunker as much as possible so you can try out the code yourself in a browser. Then you'll practice what you've learnt with either an online quiz or a set of flash cards. You are going to learn all about:- - Typescript & ES6 Javascript. - Components & Binding - Directives - Dependancy Injection & Services - Angular Modules & Bootstrapping your Angular application. - SPAs & Routing - Angular CLI - Forms - Reactive Programming with RXJs - HTTP - Unit Testing The ideal student is an existing web developer, with some JavaScript knowledge that wants to add Angular 2 to their skill set. Or perhaps you are an existing Angular 1 developer who wants to level up to Angular 2. You do need to be comfortable with at least the ES5 version of JavaScript. We'll be using a UI framework called twitter bootstrap throughout the course but you still must know HTML and some CSS.

    The clarity and eloquence of the presentation make it popular with teachers and students alike. The text aims to expand the reader's view of the field and to present standard material in a novel way. All of the most important topics in the field are covered with a fresh perspective, including iterative methods for systems of equations and eigenvalue problems and the underlying principles of conditioning and stability. Presentation is in the form of 40 lectures, which each focus on one or two central ideas. The unity between topics is emphasized throughout, with no risk of getting lost in details and technicalities. The book breaks with tradition by beginning with the QR factorization - an important and fresh idea for students, and the thread that connects most of the algorithms of numerical linear algebra.