Topics covered include matrix multiplication, row reduction, matrix inverse, orthogonality and computation. The self-teaching book is loaded with examples and graphics and provides a wide array of probing problems, accompanying solutions, and a glossary. Chapter 1: Introduction to Vectors; Chapter 2: Solving Linear Equations; Chapter 3: Vector Spaces and Subspaces; Chapter 4: Orthogonality; Chapter 5: Determinants; Chapter 6: Eigenvalues and Eigenvectors; Chapter 7: Linear Transformations; Chapter 8: Applications; Chapter 9: Numerical Linear Algebra; Chapter 10: Complex Vectors and Matrices; Solutions to Selected Exercises; Final Exam. Matrix Factorizations. Conceptual Questions for Review. Glossary: A Dictionary for Linear Algebra Index Teaching Codes Linear Algebra in a Nutshell.

    This book draws on material Michael created for his renowned Object Mentor seminars, techniques Michael has used in mentoring to help hundreds of developers, technical managers, and testers bring their legacy systems under control. The topics covered include: Understanding the mechanics of software change, adding features, fixing bugs, improving design, optimizing performance Getting legacy code into a test harness Writing tests that protect you against introducing new problems Techniques that can be used with any language or platform, with examples in Java, C++, C, and C# Accurately identifying where code changes need to be made Coping with legacy systems that aren't object-oriented Handling applications that don't seem to have any structureThis book also includes a catalog of twenty-four dependency-breaking techniques that help you work with program elements in isolation and make safer changes.

    This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915            0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)

    And through CODE, we see how this ingenuity and our very human compulsion to communicate have driven the technological innovations of the past two centuries. Using everyday objects and familiar language systems such as Braille and Morse code, author Charles Petzold weaves an illuminating narrative for anyone who’s ever wondered about the secret inner life of computers and other smart machines. It’s a cleverly illustrated and eminently comprehensible story—and along the way, you’ll discover you’ve gained a real context for understanding today’s world of PCs, digital media, and the Internet. No matter what your level of technical savvy, CODE will charm you—and perhaps even awaken the technophile within.

    A superbly practical book that explains what established businesses, public survey institutions, and new yentures have to know, have to learn, and have to do in today' s economy and marketplace.

    Stewart's Calculus is successful throughout the world because he explains the material in a way that makes sense to a wide variety of readers. His explanations make ideas come alive, and his problems challenge, to reveal the beauty of calculus. Stewart's examples stand out because they are not just models for problem solving or a means of demonstrating techniques--they also encourage readers to develp an analytic view of the subject. This edition includes new problems, examples, and projects.

    This revision includes General ChemistryNow, a new CD-ROM and web-based learning system that focuses on goals, connections, and complete integration with the text.

    This text uses a unified approach based on a single economics model that provides readers with a clear understanding of macroeconomics and its classical and Keynesian assumptions. Introduction: Introduction to Macroeconomics; The Measurement and Structure of the National Economy. Long-Run Economic Performance: Productivity, Output, and Employment; Consumption, Saving, and Investment; Saving and Investment in the Open Economy; Long-Run Economic Growth; The Asset Market, Money, and Prices. Business Cycles and Macroeconomic Policy: Business Cycles; The IS-LM/AD-AS Model: A General Framework for Macroeconomic Analysis; Classical Business Cycle Analysis: Market-Clearing Macroeconomics; Keynesianism: The Macroeconomics of Wage and Price Rigidity. Macroeconomic Policy: Its Environment and Institutions: Unemployment and Inflation; Exchange Rates, Business Cycles, and Macroeconomic Policy in the Open Economy; Monetary Policy and the Federal Reserve System; Government Spending and Its Financing. For all readers interested in intermediate macroeconomics.

    Available here:readmeaway.com/download?i=1593279523The Linux Command Line, 2nd Edition: A Complete Introduction PDF by William ShottsRead The Linux Command Line, 2nd Edition: A Complete Introduction PDF from No Starch Press,William ShottsDownload William Shotts’s PDF E-book The Linux Command Line, 2nd Edition: A Complete Introduction

    People can use economics and they can use statistics and numbers to get at the truth and there is a real appetite for doing so. This is such a BBC thing to say--there’s almost a public service mission to be fulfilled in educating people about economics. When I wrote The Undercover Economist, it was all about my pure enthusiasm for the subject; the book is full of stuff I wanted to say and that is always the thing with the books: they are always such fun to write. Do you think that people these days are generally more economically literate? People are now aware of economics for various reasons. There are the problems with the economy--there is always more interest in economics when it is all going wrong. Where is the border line in your new book between economics and sociology? I don’t draw a border line, and particularly not with the new book. The Undercover Economist was basically all the cool economics I could think of and The Logic of Life was me investigating a particular part of economics. All of the references in The Logic of Life were academic economics papers that I had related--and hopefully made more fun. This new book, Adapt, is very different. I have started by asking what is wrong with the world, what needs fixing, how does it work--and if economics can tell us something about that (which it can) then I have used it. And if economics is not the tool that you need--if you need to turn to sociology or engineering or biology or psychology--I have, in fact, turned to all of them in this book. If that’s what you need, then that’s where I have gone. So I have written this book in a different way: I started with a problem and tried to figure out how to solve it. What specific subjects do you tackle? To be a bit more specific, the book is about how difficult problems get solved and I look at quick change; the banking crisis; poverty; innovation, as I think there is an innovation slow-down; and the war in Iraq. Also, I look at both problems in business and in everyday life. Those are the big problems that I look at--and my conclusion is that these sorts of problems only ever get solved by trial and error, so when they are being solved, they are being solved through experimentation, which is often a bottom-up process. When they are not being solved it is because we are not willing to experiment, or to use trial and error. Do you think companies will change to be much more experimental, with more decisions placed in the hands of employees? I don’t think that is necessarily a trend, and the reason is that the market itself is highly experimental, so if your company isn’t experimental it may just happen to have a really great, successful idea--and that’s fine; if it doesn’t, it will go bankrupt. But that said, it is very interesting to look at the range of companies who have got very into experimentation--they range from the key-cutting chain Timpson’s to Google; you can’t get more different than those two firms, but actually the language is very similar; the recruitment policies are similar; the way the employees get paid is similar. The “strap line” of the book is that “Success always starts with failure.” You are a successful author… so what was the failure that set you up for success? I was working on a book before The Undercover Economist… it was going to be a sort of Adrian Mole/Bridget Jones’ Diary-styled fictional comedy, in which the hero was this economist and through the hilarious things that happened to him, all these economic principles would be explained--which is a great idea--but the trouble is that I am not actually funny. Another example would be my first job as a management consultant… and I was a terrible management consultant. I crashed out after a few months. Much better that, than to stick with the job for two or three years-- a lot of people say you have got to do that to “show your commitment.” Taking the job was a mistake--why would I need to show my commitment to a mistake? Better to realise you made a mistake, stop and do something else, which I did. That idea that “failure breeds success” is central to most entrepreneurs. Do you think we need more of it in the UK? I think that the real problem is not failure rates in business; the problem is failure rates in politics. We need a much higher failure rate in politics. What actually happens is politicians--and this is true of all political parties--have got some project and they’ll say, “Right, we are going to do this thing,” and it is quite likely that idea is a bad idea--because most ideas fail; the world is complicated and while I don’t have the numbers for this, most ideas are, as it turns out, not good ideas. But they never collect the data, or whatever it is they need to measure, to find out where their idea is failing. So they have this bad idea, roll this bad idea out and the bad idea sticks, costs the country hundreds, millions, or billions of pounds, and then the bad idea is finally reversed by the next party on purely ideological grounds and you never find out whether it really worked or not. So we have this very, very low willingness to collect the data that would be necessary to demonstrate failure, which is the bit we actually need. To give a brief example: Ken Livingstone, as Mayor of London, came along and introduced these long, bendy buses. Boris Johnson came along and said, “If you elect me, I am going to get rid of those big bendy buses and replace them with double-decker buses.” He was elected and he did it, so… which one of them is right? I don’t know. I mean, isn’t that crazy? I know democracy is a wonderful thing and we voted for Ken Livingstone and we voted for Boris Johnson, but it would be nice to actually have the data on passenger injury rates, how quickly people can get on and off these buses, whether disabled people are using these buses… the sort of basic evidence you would want to collect. Based on that, are you a supporter of David Cameron’s “Big Society”, which in a sense favours local experimentation over central government planning? Well, I have some sympathy for the idea of local experimentation, but what worries me is that we have to have some mechanism that is going to tell you what is working and what is not--and there is no proposal for that. Cameron’s Tories seem to have the view that ‘if it is local then it will work.’ In my book, I have all kinds of interesting case studies of situations where localism really would have worked incredibly well, as in, say, the US Army in Iraq. But I have also got examples of where localism did not work well at all--such as a corruption-fighting drive in Indonesia. Is the new book, Adapt, your movement away from economic rationalist to management guru? Are you going to cast your eye over bigger problems? The two changes in Adapt are that I have tried to start with the problem, rather than saying, “I have got a hammer--I’m going to look for a nail.” I started with a nail and said, “Ok, look, I need to get this hammered in.” So I have started with the problem and then looked anywhere for solutions. And the second thing is that I have tried to do is write with more of a narrative. This is not a Malcolm Gladwell book, but I really admire the way that people like Gladwell get quite complex ideas across because they get you interested in the story; that is something that I have tried to do more of here. I am not too worried about it, because I know that I am never going to turn into Malcolm Gladwell--I am always going to be Tim Harford--but it doesn’t hurt to nudge in a certain direction. On Amazon, we recommend new book ideas to people: “If you like Tim Harford you may like…”, but what does Tim Harford also like? I read a lot of books, mostly non-fiction and in two categories: people who I think write a lot better than I do, and people who think about economics more deeply than I do. In the first category I am reading people like Michael Lewis, Kathryn Schulz (I loved her first book, Being Wrong), Malcolm Gladwell and Alain de Botton. In the second category, I read lots of technical economics books, but I enjoy Steven Landsburg, Edward Glaeser (who has a book out now which looks good), Bill Easterly… I don’t necessarily agree with all of these people! When I am not reading non-fiction, I am reading comic books or 1980s fantasy authors like Jack Vance.

    But if code isn't clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn't have to be that way. Noted software expert Robert C. Martin presents a revolutionary paradigm with Clean Code: A Handbook of Agile Software Craftsmanship . Martin has teamed up with his colleagues from Object Mentor to distill their best agile practice of cleaning code on the fly into a book that will instill within you the values of a software craftsman and make you a better programmer but only if you work at it. What kind of work will you be doing? You'll be reading code - lots of code. And you will be challenged to think about what's right about that code, and what's wrong with it. More importantly, you will be challenged to reassess your professional values and your commitment to your craft. Clean Code is divided into three parts. The first describes the principles, patterns, and practices of writing clean code. The second part consists of several case studies of increasing complexity. Each case study is an exercise in cleaning up code - of transforming a code base that has some problems into one that is sound and efficient. The third part is the payoff: a single chapter containing a list of heuristics and "smells" gathered while creating the case studies. The result is a knowledge base that describes the way we think when we write, read, and clean code. Readers will come away from this book understanding ‣ How to tell the difference between good and bad code‣ How to write good code and how to transform bad code into good code‣ How to create good names, good functions, good objects, and good classes‣ How to format code for maximum readability ‣ How to implement complete error handling without obscuring code logic ‣ How to unit test and practice test-driven development This book is a must for any developer, software engineer, project manager, team lead, or systems analyst with an interest in producing better code.

    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

    It happens because VCs are experts in financings and most entrepreneurs are not. Brad and Jason are out to fix that problem with Venture Deals. This book is long overdue and badly needed."—Fred Wilson, Managing Partner, Union Square Ventures"Feld and Mendelson pack a graduate-level course into this energetic and accessible book.?The authors' frank style and incisive insight make this a must-read for high-growth company entrepreneurs, early-stage investors, and graduate students.?Start here if you want to understand venture capital deal structure and strategies.?I enthusiastically recommend."—Brad Bernthal, CU Boulder, Associate Clinical Professor ofLaw, Technology Policy, Entrepreneurial Law"A must-read book for entrepreneurs.?Brad and Jason demystify the overly complex world of term sheets and M&A, cutting through the legalese and focusing on what really matters.?That's a good thing not just for entrepreneurs, but also for venture capitalists, angels, and lawyers.?Having an educated entrepreneur on the other side of the table means you spend your time negotiating the important issues and ultimately get to the right deal faster."—Greg Gottesman, Managing Director, Madrona Venture Group"Venture Deals is a must-read for any entrepreneur contemplating or currently leading a venture-backed company. Brad and Jason are highly respected investors who shoot straight from the hip and tell it like it is, bringing a level of transparency to a process that is rarely well understood. It's like having a venture capitalist as a best friend who is looking out for your best interests and happy to answer all of your questions."—Emily Mendell, Vice President of Communications,National Venture Capital Association"The adventure of starting and growing a company can be exhilarating or excruciating—or both. Feld and Mendelson have done a masterful job of shedding light on what can either become one of the most helpful or dreadful experiences for entrepreneurs—accepting venture capital into their firm. This book takes the lid off the black box and helps entrepreneurs understand the economics and control provisions of working with a venture partner."—Lesa Mitchell, Vice President, Advancing Innovation, Kauffman Foundation

    RWJ took a hard look at what was truly important and useful; in doing so, they eliminated topics of dubious relevance, downplayed purely theoretical issues, and minimized the use of extensive and elaborate calculations to illustrate points that are either intuitively obvious or of limited practical use. As a result of this process, three basic themes became the central focus of FCF: An Emphasis on Intuition, A Unified Valuation Approach, and A Managerial Focus. And remember, every text purchased from Irwin/McGraw Hill comes packaged free with F.A.S.T. software, and calculator supplement cards.

     -Byte, September 1995 I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me! I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up. -Charles Long If you think you're a really good programmer... read [Knuth's] Art of Computer Programming... You should definitely send me a resume if you can read the whole thing. -Bill Gates It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers. -Jonathan Laventhol This first volume in the series begins with basic programming concepts and techniques, then focuses more particularly on information structures-the representation of information inside a computer, the structural relationships between data elements and how to deal with them efficiently. Elementary applications are given to simulation, numerical methods, symbolic computing, software and system design. Dozens of simple and important algorithms and techniques have been added to those of the previous edition. The section on mathematical preliminaries has been extensively revised to match present trends in research. Ebook (PDF version) produced by Mathematical Sciences Publishers (MSP), http: //msp.org