He dissects the global relationships between equities, bonds, currencies, and commodities like no one else can, and lays out an irrefutable case for intermarket analysis in plain English. This book is a must-read for all serious traders." -Louis B. Mendelsohn, creator of VantagePoint Intermarket Analysis software "John Murphy's Intermarket Analysis should be on the desk of every trader and investor if they want to be positioned in the right markets at the right time." -Thom Hartle, President, Market Analytics, Inc. (www.thomhartle.com) "This book is full of valuable information. As a daily practitioner of intermarket analysis, I thought I knew most aspects of this invaluable subject, but this book gave me several new ideas. I thoroughly recommend it for beginners and professionals." -Martin Pring, President of Pring.com and editor of the Intermarket Review Newsletter "Mr. Murphy's Intermarket Analysis is truly the most efficient and unambiguous way to define economic and fundamental relationships as they unfold in the market. It cuts through all of the conflicting economic news/views expressed each day to provide a clear picture of the 'here and now' in the global marketplace." -Dennis Hynes, Managing Director, R. W. Pressprich "Master Murphy is back with the quintessential look at intermarket analysis. The complex relationships among financial instruments have never been more important, and this book brings it all into focus. This is an essential read for all investors." -Andrew Bekoff, Technical Strategist, VDM NYSE Specialists "John Murphy is a legend in technical analysis, and a master at explaining precisely how the major markets impact each other. This updated version provides even more lessons from the past, plus fresh insights on current market trends." -Price Headley, BigTrends.com, author of Big Trends in Trading

    Sullivan Elin M. Wicks C. Patrick Koelling   A succinct job description for an engineer consists of just two words: problem solver. Broadly speaking, engineers use knowledge to find new ways of doing things economically. Engineering design solutions do not exist in a vacuum, but within the context of a business opportunity. Truly, every problem has multiple solutions, so the question is, “How does one rationally select the design solution with the most favorable economic result?” The answer to this question can also be put forth in two words: engineering economy. This field of engineering provides a systematic framework for evaluating the economic aspects of competing design solutions. Just as engineers model the stress on a support column or the thermodynamic properties of a steam turbine, they must also model the economic impact of their engineering recommendations. Engineering economy is the subject of this textbook.   Highlights of Engineering Economy, Fourteenth Edition: ×           Fifty percent of end-of-chapter problems are new or revised. ×           A bank of algorithmically generated test questions is available to adopting instructors. ×           Fundamentals of Engineering (FE) exam-style questions are included among the end-of-chapter problem sets. ×           Spreadsheet models are integratedthroughout. ×           An appendix on the basics of accounting is included in Chapter 2. ×           Chapter 3 on Cost Estimation appears early in the book. ×           An appendix on techniques for using Excel in engineering economy is available for reference. ×           Numerous comprehensive examples and case studies appear throughout the book. ×           Extended learning exercises appear in most chapters. ×           Personal finance problems are featured in most chapters. ×           Many pointers to relevant Web sites are provided.   ISBN-13: 978-0-13-614297-3 ISBN-10: 0-13-614297-4

    Reviewed are fundamental statistical concepts--such as correlation, regressions, data preparation and screening, path analysis, and confirmatory factor analysis--as well as more advanced methods, including the evaluation of nonlinear effects, measurement models and structural regression models, latent growth models, and multilevel SEM. The companion Web page offers data and program syntax files for many of the research examples, electronic overheads that can be downloaded and printed by instructors or students, and links to SEM-related resources.

    The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.Theory Backed up by Practical ExamplesThe book covers neural networks, graphical models, reinforcement learning, evolutionary algorithms, dimensionality reduction methods, and the important area of optimization. It treads the fine line between adequate academic rigor and overwhelming students with equations and mathematical concepts. The author addresses the topics in a practical way while providing complete information and references where other expositions can be found. He includes examples based on widely available datasets and practical and theoretical problems to test understanding and application of the material. The book describes algorithms with code examples backed up by a website that provides working implementations in Python. The author uses data from a variety of applications to demonstrate the methods and includes practical problems for students to solve.Highlights a Range of Disciplines and ApplicationsDrawing from computer science, statistics, mathematics, and engineering, the multidisciplinary nature of machine learning is underscored by its applicability to areas ranging from finance to biology and medicine to physics and chemistry. Written in an easily accessible style, this book bridges the gaps between disciplines, providing the ideal blend of theory and practical, applicable knowledge."

    Previously undocumented, these 23 patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves.The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently. Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.

    Provides a review of introductory noncalculus-based physics for those who do not have a strong background in mathematics.

    Is it Rita's years of PMP exam preparation experience? The endless hours of ongoing research? The interviews with project managers who failed the exam, to identify gaps in their knowledge? Or is it the razor-sharp focus on making sure project managers don't waste a single minute of their time studying any more than they absolutely have to? Actually, it's all of the above. PMP Exam Prep, Sixth Edition by Rita Mulcahy contains hundreds of updates and improvements from previous editions--including new exercises and sample questions never before in print. Offering hundreds of sample questions, critical time-saving tips plus games and activities available nowhere else, this book will help you pass the PMP exam on your first try.

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    Douglas Hubbard helps us create a path to know the answer to almost any question in business, in science, or in life . . . Hubbard helps us by showing us that when we seek metrics to solve problems, we are really trying to know something better than we know it now. How to Measure Anything provides just the tools most of us need to measure anything better, to gain that insight, to make progress, and to succeed." -Peter Tippett, PhD, M.D. Chief Technology Officer at CyberTrust and inventor of the first antivirus software "Doug Hubbard has provided an easy-to-read, demystifying explanation of how managers can inform themselves to make less risky, more profitable business decisions. We encourage our clients to try his powerful, practical techniques." -Peter Schay EVP and COO of The Advisory Council "As a reader you soon realize that actually everything can be measured while learning how to measure only what matters. This book cuts through conventional cliches and business rhetoric and offers practical steps to using measurements as a tool for better decision making. Hubbard bridges the gaps to make college statistics relevant and valuable for business decisions." -Ray Gilbert EVP Lucent "This book is remarkable in its range of measurement applications and its clarity of style. A must-read for every professional who has ever exclaimed, 'Sure, that concept is important, but can we measure it?'" -Dr. Jack Stenner Cofounder and CEO of MetraMetrics, Inc.

    It reveals the attraction that has drawn leading mathematicians and amateurs alike to number theory over the course of history.

    Featuring Gerber's signature easy-to-understand, easy-to-implement style, The E-Myth Attorney features:A complete start-up guide you can use to get your practice off the ground quickly, as well as comprehensive action steps for maximizing the performance of an existing practice Industry specific advice from two recognized legal experts that have developed a highly successful legal practice using Gerber's principles Gerber's universal appeal as a recognized expert on small businesses who has coached, taught, and trained over 60,000 small businesses The E-Myth Attorney is the last guide you'll ever need to make the difference in building or developing your successful legal practice.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    This book takes you beyond the currency ("Blockchain 1.0") and smart contracts ("Blockchain 2.0") to demonstrate how the blockchain is in position to become the fifth disruptive computing paradigm after mainframes, PCs, the Internet, and mobile/social networking. Author Melanie Swan, Founder of the Institute for Blockchain Studies, explains that the blockchain is essentially a public ledger with potential as a worldwide, decentralized record for the registration, inventory, and transfer of all assets—not just finances, but property and intangible assets such as votes, software, health data, and ideas. Topics include: Concepts, features, and functionality of Bitcoin and the blockchain Using the blockchain for automated tracking of all digital endeavors Enabling censorship?resistant organizational models Creating a decentralized digital repository to verify identity Possibility of cheaper, more efficient services traditionally provided by nations Blockchain for science: making better use of the data-mining network Personal health record storage, including access to one’s own genomic data Open access academic publishing on the blockchain This book is part of an ongoing O’Reilly series. Mastering Bitcoin: Unlocking Digital Crypto-Currencies introduces Bitcoin and describes the technology behind Bitcoin and the blockchain. Blockchain: Blueprint for a New Economy considers theoretical, philosophical, and societal impact of cryptocurrencies and blockchain technologies.

    Now revised and updated to include expanded coverage of monetary policy, this volume traces the history of macroeconomics and the evolution of macroeconomic thought and the resulting theory and policy.

    It is a great book, not just for beginning programmers, but also for computer users who would want to have an idea what is happening behind the scenes as they work with various computer programs. In this book, you are going to learn what the C programming language entails, how to write conditions, expressions, statements and even commands, for the language to perform its functions efficiently. You will learn too how to organize relevant expressions so that after compilation and execution, the computer returns useful results and not error messages. Additionally, this book details the data types that you need for the C language and how to present it as well. Simply put, this is a book for programmers, learners taking other computer courses, and other computer users who would like to be versed with the workings of the most popular computer language, C. In this book You'll learn: What Is The C Language? Setting Up Your Local Environment The C Structure and Data Type C Constants and Literals C Storage Classes Making Decisions In C The Role Of Loops In C Programming Functions in C Programming Structures and Union in C Bit Fields and Typedef Within C. C Header Files and Type Casting Benefits Of Using The C Language ...and much more!! Download your copy today! click the BUY button and download it right now!