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.

    This book is going to provide you with everything you need to know about Ethereum and whether it is worth investing in now. Like many people, I became interested in Bitcoin years ago, when Bitcoin was still relatively new, but hinting at a huge profit margin for those who took the risk and invested. It was after a couple of years playing around on the Bitcoin market that I heard about a new type of blockchain technology, one that wasn’t just a digital form of payment, but one that could support potentially endless different types of applications. Not only that, but it comes with its own currency. This, to me, sounded like a potentially profitable situation, so I decided to dig a little deeper. Unlike Bitcoin, Ethereum is still largely unknown to those who don’t keep up with the cryptocurrency world, so the amount of information available is limited or highly technical. Still, it was fascinating and the more I read about Ethereum, the more I began to see its huge potential. And I’m not alone. More and more Fortune 500 companies are investing in Ethereum technology as it becomes increasingly lucrative and poises to change business processes as we know them. I decided to condense my research and share my knowledge on Ethereum by writing this book. The book is designed for those who are new to cryptocurrency, but want to invest in it or learn more about it, as well as for more experienced traders looking to expand their portfolios. With a 5,000% increase in value in the first few months of 2017, Ethereum is proving to be a profitable currency. Still, as it is so new – it was only launched in 2015 – it comes with many infancy-related risks. It’s partly this that makes it so exciting. This book will help you make your own investment decisions and decide if Ethereum is the right coin for you after weighing up the pros and cons that are presented here. So far, Ethereum has made me good money and I was lucky to make the investment when I did. However, now is not too late to invest, not by a long shot. In fact, now is the perfect moment to make the most of Ethereum’s infancy and gain potential first-mover advantages. Ethereum’s technology is only at the beginning of its potential growth stages, possibly reaching to dozens of industries and thousands of services. If its technology is adopted the way it is expected to be, Ethereum will enjoy a long and lucrative spot at the top. The profits are ripe for the taking. Here Is A Preview Of What’s Included… What Is Ethereum? Smart Contracts, Dapps, And DAOs The Technology Behind Ethereum What Is Ethereum Mining? Uses Of Ethereum What Is Ether? The Financial History Of Ether How to Buy, Sell, And Store Ether The Mining Process Of Ether Should I Invest In Ether? The Future Of Ethereum Much, Much More! Get your copy today!

    … The book the National Security Agency wanted never to be published." –Wired Magazine "…monumental… fascinating… comprehensive… the definitive work on cryptography for computer programmers…" –Dr. Dobb's Journal"…easily ranks as one of the most authoritative in its field." —PC Magazine"…the bible of code hackers." –The Millennium Whole Earth CatalogThis new edition of the cryptography classic provides you with a comprehensive survey of modern cryptography. The book details how programmers and electronic communications professionals can use cryptography—the technique of enciphering and deciphering messages-to maintain the privacy of computer data. It describes dozens of cryptography algorithms, gives practical advice on how to implement them into cryptographic software, and shows how they can be used to solve security problems. Covering the latest developments in practical cryptographic techniques, this new edition shows programmers who design computer applications, networks, and storage systems how they can build security into their software and systems. What's new in the Second Edition? * New information on the Clipper Chip, including ways to defeat the key escrow mechanism * New encryption algorithms, including algorithms from the former Soviet Union and South Africa, and the RC4 stream cipher * The latest protocols for digital signatures, authentication, secure elections, digital cash, and more * More detailed information on key management and cryptographic implementations

    In this book, Agile Alliance cofounder Mike Cohn discusses the philosophy of agile estimating and planning and shows you exactly how to get the job done, with real-world examples and case studies.Concepts are clearly illustrated and readers are guided, step by step, toward how to answer the following questions: What will we build? How big will it be? When must it be done? How much can I really complete by then? You will first learn what makes a good plan-and then what makes it agile.Using the techniques in Agile Estimating and Planning , you can stay agile from start to finish, saving time, conserving resources, and accomplishing more. Highlights include:Why conventional prescriptive planning fails and why agile planning works How to estimate feature size using story points and ideal days--and when to use each How and when to re-estimate How to prioritize features using both financial and nonfinancial approaches How to split large features into smaller, more manageable ones How to plan iterations and predict your team's initial rate of progress How to schedule projects that have unusually high uncertainty or schedule-related risk How to estimate projects that will be worked on by multiple teams Agile Estimating and Planning supports any agile, semiagile, or iterative process, including Scrum, XP, Feature-Driven Development, Crystal, Adaptive Software Development, DSDM, Unified Process, and many more. It will be an indispensable resource for every development manager, team leader, and team member.

    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.

    These secrets will help you get great salary raises, get selected in a job interview, & even get a promotion easily. Here are the closely-guarded secrets that will be revealed in this never-before disclosure. Career Secret # 1: Why would you be fired? Can you avoid the dreaded Pink Slip? And why the most-beloved perk 'Work From Home' is the surest ticket out of the company? For the first time ever, you will be taken behind the scenes of a mass-firing (multiple layoffs). You will understand what prompts a company to fire its loyal employees (this means you). And the biggest insider secret... if you are Working from Home, why you will get laid off in the next few months. You will also learn how to protect your job & make yourself almost 'fire'proof. Career Secret # 2: Job sites are utterly useless Sick and tired of job hunting? Learn why job sites are utterly useless & where you need to focus your energies for a job search. This one strategy will increase your probability of getting a job from a measly 1% to a stunning 60%. Career Secret # 3: Your experience or skills doesn't matter in an Interview! Did you know that your experience or skills doesn't count for the hiring manager? What is the recruiter really looking for? It's this one little thing... Career Secret # 4: Your manager doesn't care what you did the whole year Are you surprised? Or did I confirm what you already suspected? Is everything you are doing in your job, all in vain? Not yet. This secret will tell you how to get on your manager's radar. Career Secret # 5: Appraisal ratings and increments are your manager's headache. Here's how to force your manager to give you a fat paycheck. There is a ton of information on salary negotiation during a job interview. What about salary negotiation during a performance review? This secret will tell you the simplest & easiest way to rate your own performance. And how to make an epic presentation that will force your manager to grudgingly give you a great rating & an excellent salary raise.

    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.

    What makes an operating system modern? According to author Andrew Tanenbaum, it is the awareness of high-demand computer applications--primarily in the areas of multimedia, parallel and distributed computing, and security. The development of faster and more advanced hardware has driven progress in software, including enhancements to the operating system. It is one thing to run an old operating system on current hardware, and another to effectively leverage current hardware to best serve modern software applications. If you don't believe it, install Windows 3.0 on a modern PC and try surfing the Internet or burning a CD. Readers familiar with Tanenbaum's previous text, Operating Systems, know the author is a great proponent of simple design and hands-on experimentation. His earlier book came bundled with the source code for an operating system called Minux, a simple variant of Unix and the platform used by Linus Torvalds to develop Linux. Although this book does not come with any source code, he illustrates many of his points with code fragments (C, usually with Unix system calls). The first half of Modern Operating Systems focuses on traditional operating systems concepts: processes, deadlocks, memory management, I/O, and file systems. There is nothing groundbreaking in these early chapters, but all topics are well covered, each including sections on current research and a set of student problems. It is enlightening to read Tanenbaum's explanations of the design decisions made by past operating systems gurus, including his view that additional research on the problem of deadlocks is impractical except for "keeping otherwise unemployed graph theorists off the streets." It is the second half of the book that differentiates itself from older operating systems texts. Here, each chapter describes an element of what constitutes a modern operating system--awareness of multimedia applications, multiple processors, computer networks, and a high level of security. The chapter on multimedia functionality focuses on such features as handling massive files and providing video-on-demand. Included in the discussion on multiprocessor platforms are clustered computers and distributed computing. Finally, the importance of security is discussed--a lively enumeration of the scores of ways operating systems can be vulnerable to attack, from password security to computer viruses and Internet worms. Included at the end of the book are case studies of two popular operating systems: Unix/Linux and Windows 2000. There is a bias toward the Unix/Linux approach, not surprising given the author's experience and academic bent, but this bias does not detract from Tanenbaum's analysis. Both operating systems are dissected, describing how each implements processes, file systems, memory management, and other operating system fundamentals. Tanenbaum's mantra is simple, accessible operating system design. Given that modern operating systems have extensive features, he is forced to reconcile physical size with simplicity. Toward this end, he makes frequent references to the Frederick Brooks classic The Mythical Man-Month for wisdom on managing large, complex software development projects. He finds both Windows 2000 and Unix/Linux guilty of being too complicated--with a particular skewering of Windows 2000 and its "mammoth Win32 API." A primary culprit is the attempt to make operating systems more "user-friendly," which Tanenbaum views as an excuse for bloated code. The solution is to have smart people, the smallest possible team, and well-defined interactions between various operating systems components. Future operating system design will benefit if the advice in this book is taken to heart. --Pete Ostenson

    But many organizations adopting these technologies have found that it only leads to a faster-growing sprawl of unmanageable systems. This is where infrastructure as code can help. With this practical guide, author Kief Morris of ThoughtWorks shows you how to effectively use principles, practices, and patterns pioneered through the DevOps movement to manage cloud age infrastructure.Ideal for system administrators, infrastructure engineers, team leads, and architects, this book demonstrates various tools, techniques, and patterns you can use to implement infrastructure as code. In three parts, you'll learn about the platforms and tooling involved in creating and configuring infrastructure elements, patterns for using these tools, and practices for making infrastructure as code work in your environment.Examine the pitfalls that organizations fall into when adopting the new generation of infrastructure technologiesUnderstand the capabilities and service models of dynamic infrastructure platformsLearn about tools that provide, provision, and configure core infrastructure resourcesExplore services and tools for managing a dynamic infrastructureLearn specific patterns and practices for provisioning servers, building server templates, and updating running servers

    It is also the most powerful, and in some ways, the most confusing. What do accessible, content-focused standards-based web designers and front-end developers need to know? And how can we harness the power of HTML5 in today’s browsers?In this brilliant and entertaining user’s guide, Jeremy Keith cuts to the chase, with crisp, clear, practical examples, and his patented twinkle and charm.

    It is a conversational book that feels easy and informative. This short and lucid book covers everything important, with concrete examples, and invites the reader to join this field. The chapters in the book are organized for a typical one-semester course. The book contains case-lets from real-world stories at the beginning of every chapter. There is a running case study across the chapters as exercises. This book is designed to provide a student with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms. Students across a variety of academic disciplines, including business, computer science, statistics, engineering, and others are attracted to the idea of discovering new insights and ideas from data. This book can also be gainfully used by executives, managers, analysts, professors, doctors, accountants, and other professionals to learn how to make sense of the data coming their way. This is a lucid flowing book that one can finish in one sitting, or can return to it again and again for insights and techniques. Table of Contents Chapter 1: Wholeness of Business Intelligence and Data Mining Chapter 2: Business Intelligence Concepts & Applications Chapter 3: Data Warehousing Chapter 4: Data Mining Chapter 5: Decision Trees Chapter 6: Regression Models Chapter 7: Artificial Neural Networks Chapter 8: Cluster Analysis Chapter 9: Association Rule Mining Chapter 10: Text Mining Chapter 11: Web Mining Chapter 12: Big Data Chapter 13: Data Modeling Primer Appendix: Data Mining Tutorial using Weka

    Salesforce.com (more than 50%) and Twitter (more than 75% fall into this category. Ebay gets more than 8 billion API calls a month. Facebook and Google, have dozens of APIs that enable both free services and e-commerce, get more than 5 billion API calls each day. Other companies like NetFlix have expanded their service of streaming movies over the the web to dozens of devices using API. At peak times, more than 20 percent of all traffic is accounted for by Netflix through its APIs. Companies like Sears and E-Trade are opening up their catalogs and other services to allow developers and entrepreneurs to create new marketing experiences. Making an API work to create a new channel is not just a matter of technology. An API must be considered in terms of business strategy, marketing, and operations as well as the technical aspects of programming. This book, written by Greg Brail, CTO of Apigee, and Brian Mulloy, VP of Products, captures the knowledge of all these areas gained by Apigee, the leading company in supporting the rollout of high traffic APIs.

    The book assumes no prior knowledge of computer programming and progressively covers all the essential steps needed to become confident and proficient in using R within a day. Topics include how to input, manipulate, format, iterate (loop), query, perform basic statistics on, and plot data, via a step-by-step technique and demonstrations using in-built datasets which the reader is encouraged to replicate on their computer. Each chapter also includes exercises (with solutions) to practice key skills and empower the reader to build on the essentials gained during this introductory course.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    In the author's view, it marks the beginning of the last and perhaps most important interview phase - a phase so important that failing to prepare properly for it can undo all your hard work, including providing great answers to tough questions! It's your moment to shine - to show off the depth and breadth of your research, to remind the interviewer of how perfectly your credentials fit the job description, and to actually ask for the job! From what to ask, when to ask it, and the kind of answers to expect, this book gives every candidate, from first-timers to seasoned pros, the practical information and advice they need to ace the entire interview and get their dream job. No questions? No way!