Yeah, even the government comes crying. When those that hunt the thing that go bump in the night become the hunted, he's the one that bumps back.But nobody likes the guy because they don’t know what to expect. After all, he wakes up a new man every morning. Then there's the relatives. Being the grandson of a Fury wins him no popularity contests amongst those in the know. And the rest of his heritage being a big freaking blank isn't of help either.He takes no favorites. In the battles between the supernaturals, he’s neutral. Picking sides in a twenty or thirty-sided conflict is plain crap. Even his family pays for his help.When there’s a fuck-up that others won’t touch, you go to the Mongrel. And you’d better bring your life savings with you—he don’t work for short pay.So who’s this Mongrel, you ask? That'd be Me

    Fueled by the authors' conviction that skills inform principles; principles inform skills, Interpersonal Communication: Relating to Others maintains a careful balance between theoretical and skills-oriented material. This book integrates a key emphasis on diversity with examples drawn from a variety of age and ethnic groups and special boxes that focus on gender and diversity issues. A chapter on intercultural communication supplements this integral material by relating it to the other-oriented approach

    The new edition, fully updated with the most recent data and research possible, includes new coverage of the Medicare drug benefit, changes in the tax code, Hurricane Katrina, and the ongoing debate over privatization.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    Companies that think winning their business is a simple matter of creating a Twitter account and applying outdated notions of "cool" to their advertising are due for a rude awakening. "Marketing to Millennials "is both an enlightening look at this generation of consumers and a practical plan for earning their trust and loyalty. Based on original market research, the book reveals the eight attitudes shared by most Millennials, as well as the new rules for engaging them successfully. Millennials: - Value social networking and aren't shy about sharing opinions - Refuse to remain passive consumers--they expect to participate in product development and marketing - Demand authenticity and transparency - Are highly influential--swaying parents "and" peers - Are not all alike--understanding key segments is invaluable Featuring expert interviews and profiles of brands doing Millennial marketing right, this eye-opening book is the key to persuading the customers who will determine the bottom line for decades to come.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

    Learn the importance of obedience to God's Word in planting seed for finances.

    Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.

    Included are step-by-step instructions on how to carry out Bayesian data analyses.Download Link : readbux.com/download?i=0124058884            0124058884 Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan PDF by John Kruschke

    The authors have taken the mystery out of complex queries and explained principles and techniques with such clarity that a "Mere Mortal" will indeed be empowered to perform the superhuman. Do not walk past this book "--Graham Mandeno, Database Consultant""SQL Queries for Mere Mortals" provides a step-by-step, easy-to-read introduction to writing SQL queries. It includes hundreds of examples with detailed explanations. This book provides the tools you need to understand, modify, and create SQL queries"--Keith W. Hare, Convenor, ISO/IEC JTC1 SC32 WG3--the International SQL Standards Committee"I learned SQL primarily from the first edition of this book, and I am pleased to see a second edition of this book so that others can continue to benefit from its organized presentation of the language. Starting from how to design your tables so that SQL can be effective (a common problem for database beginners), and then continuing through the various aspects of SQL construction and capabilities, the reader can become a moderate expert upon completing the book and its samples. Learning how to convert a question in English into a meaningful SQL statement will greatly facilitate your mastery of the language. Numerous examples from real life will help you visualize how to use SQL to answer the questions about the data in your database. Just one of the "watch out for this trap" items will save you more than the cost of the book when you avoid that problem when writing your queries. I highly recommend this book if you want to tap the full potential of your database."--Kenneth D. Snell, Ph.D., Database Designer/Programmer"I don't think they do this in public schools any more, and it is a shame, but do you remember in the seventh and eighth grades when you learned to diagram a sentence? Those of you who do may no longer remember how you did it, but all of you do write better sentences because of it. John Viescas and Mike Hernandez must have remembered because they take everyday English queries and literally translate them into SQL. This is an important book for all database designers. It takes the complexity of mathematical Set Theory and of First Order Predicate Logic, as outlined in E. F. Codd's original treatise on relational database design, and makes it easy for anyone to understand. If you want an elementary- through intermediate-level course on SQL, this is the one book that is a requirement, no matter how many others you buy."--Arvin Meyer, MCP, MVP"Even in this day of wizards and code generators, successful database developers still require a sound knowledge of Structured Query Language (SQL, the standard language for communicating with most database systems). In this book, John and Mike do a marvelous job of making what's usually a dry and difficult subject come alive, presenting the material with humor in a logical manner, with plenty of relevant examples. I would say that this book should feature prominently in the collection on the bookshelf of all serious developers, except that I'm sure it'll get so much use that it won't spend much time on the shelf "-- Doug Steele, Microsoft Access Developer and author"Over the last several decades, SQL has evolved from a language known only to computer specialists to a widely used international standard of the computer industry. The number of new applications deployed each year using SQL now totals in the millions. If you are accessing corporate information from the Internet or from an internal network, you are probably using SQL. This new edition of "SQL Queries for Mere Mortals" helps new users learn the foundations of SQL queries, and is an essential reference guide for intermediate and advanced users.The accompanying CD contains five sample databases used for the example queries throughout the book in four different formats: Microsoft SQL Server 2000 and later, Microsoft Access 2000 and later, MySQL version 5.0 and later, and SQL scripts that can be used with most other implementations of the language.

    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.

    Joining together with a wizard, a druid, a necromancer, and a crusader, Morbed has arrived at a remote island to track down an elusive vagabond andreclaim valuable items pilfered from the city of Westmarch.But there is something loose on the island, something that has killed and is very close to killing again. In order to leave the island alive, Morbed will be forced to confront not only the terrifying creature that stalks the forests, but the darkest corners of his own spirit as well.

    Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.