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.

    It covers the historic 2008 Presidential campaign and election while looking ahead to assess what the shifting political winds have in store for the future of the major political parties and Americans' political views.

    Readerswill find information on frequency distributions; mean, median, and mode; range, variance, and standard deviation;probability; and more.-Emphasizes Microsoft Excel for number-crunching and computationsDownload a sample chapter.

    Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

    Evidence for the growing significance of logotherapy includes institutes, societies and professorships in many countries of the world, as well as conferences and publications. On the Theory and Therapy of Neuroses: An Introduction to Logotherapy and Existential Analysis, the translation of Viktor Frankl's Theorie und Therapie der Neurosen by James M. DuBois, will allow for the first time English-only readers to experience this essential text on logotherapy.

    With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

    In this short book, I'll share with you what Ikigai is, why you should learn and pursue it, and how to go about discovering your Ikigai. By the end of the book, you'll be in a very good position to start discovering and pursuing your Ikigai en route to a life of joy and fulfillment. Scroll up and click "Buy now with 1-Click" to download your copy now! © 2017 All Rights Reserved!Tags: ikigai, ikigai book, ikigai kindle, ikigai the japanese secret, book ikigai, about ikigai, finding your ikigai.

    Cutting-edge international finance issues are presented along with a traditional treatment of international financial management.

    Important projects tend to be time constrained, pose huge technical challenges, and suffer from a lack of adequate resources. It's no wonder that project managers are increasingly focusing their attention on risk identification.Identifying and Managing Project Risk is a practical guide to minimizing the possibility of failure in critical projects. The book takes readers step by step through every phase of a project, showing them how to consider the possible risks involved at every point in the process. Relevant figures and diagrams support the text and illustrate key scenarios. At the end of each chapter is an analysis of how the principles just discussed applied to a supreme example of what many once considered a truly impossible project: the building of the Panama Canal.Packed with real-world information, this book is essential reading for any project manager seeking to complete projects smoothly and successfully."

    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.

    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.

    If you're a business or IT professional, this short hands-on guide teaches you how to pull and transform data with SQL in significant ways. You will quickly master the fundamentals of SQL and learn how to create your own databases.Author Thomas Nield provides exercises throughout the book to help you practice your newfound SQL skills at home, without having to use a database server environment. Not only will you learn how to use key SQL statements to find and manipulate your data, but you'll also discover how to efficiently design and manage databases to meet your needs.You'll also learn how to:Explore relational databases, including lightweight and centralized modelsUse SQLite and SQLiteStudio to create lightweight databases in minutesQuery and transform data in meaningful ways by using SELECT, WHERE, GROUP BY, and ORDER BYJoin tables to get a more complete view of your business dataBuild your own tables and centralized databases by using normalized design principlesManage data by learning how to INSERT, DELETE, and UPDATE records

    "Machine learning," the process of automating tasks once considered the domain of highly-trained analysts and mathematicians, is the key to efficiently extracting useful information from this sea of raw data. Machine Learning in Action is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, the author uses the flexible Python programming language to show how to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification.

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    From arid land to verdantfields, from jungles with glimpses of elephants and tigersto tea gardens…Along the way, he meets a yogi and his singing goat, exploresancient caves, is frightened in a wild life sanctuary, sees aschizophrenic bicycle and helps a police inspector overcomehis stammering problem. A variety of experiences later, heis finally in Thimpu where a Buddhist monk reveals theroad-map to being happy.A funny, honest and entertaining real-life adventure storythat promises to surprise, shock and perhaps even liberate!