During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    Wouldn't it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships.Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers Details tools that can be used to visualize data-native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator Contains numerous examples and descriptions of patterns and outliers and explains how to show them Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.

    The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject.

    Now thoroughly updated and revised with information about all aspects of survey research?grounded in the most current research?the new edition provides practical ?how-to? guidelines on optimally using the Internet, mail, and phone channels to your advantage.

    Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    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.

    How can you be sure which methodology is appropriate, or whether your chosen combination of methods is consistent with the theoretical perspective you want to take? This book links methodology and theory with great clarity and precision, showing students and researchers how to navigate the maze of conflicting terminology. The major epistemological stances and theoretical perspectives that colour and shape current social research are detailed and the author reveals the philosophical origins of these schools of inquiry and shows how various disciplines contribute to the practice of social research as it is known today.

    Without undermining individual Bible study, private prayer, and meditation, the authors emphasize these pursuits for the purpose of both personal and community enrichment-that the whole body, as well as the individual, may be built up.Part 1 lays the groundwork of spiritual formation. Jonathan Morrow develops a distinctively evangelical theology, while Richard Averbeck writes about worship. Then Gordon Johnston and Darrell Bock delve into the text of Scripture, grounding the pursuit of spiritual formation in revealed truth.Part 2 focuses on functional aspects of spiritual formation. Klaus Issler emphasizes the importance of the heart in spiritual formation, while Reid Kisling illustrates the vital connection between character development and spiritual formation. Bill Miller explores love's role as the motivation for spiritual formation. Andrew Seidel examines servant leadership, and George Hillman extends the discussion to include the significance of calling. Gail Seidel discusses personal narrative as a catalyst for spiritual formation, and in closing, Harry Shields advocates the public preaching of the Word as a tool for spiritual formation.

    It draws on Robert Weiss's thirty years of experience in interviewing and teaching others how to do it. The most effective interviews, says Weiss, rely on creating cooperation -- an open and trusting alliance between interviewer and respondent, dedicated to specific and honest accounts of both internal and external events. Against the eclectic background of his work in national sample surveys, studies based on semi-structured interviewing, and participant observation, Weiss walks the reader through the method of qualitative interview studies: sample selection, development of an interview guide, the conduct of the interview, analysis, and preparation of the data. Weiss gives examples of successful and less successful interviews and offers specific techniques and guidelines for the practitioner.

    Yalom's The Theory and Practice of Group Psychotherapy has been the standard text in the field for decades.In this completely revised and updated fifth edition, Dr. Yalom and his collaborator Dr. Molyn Leszcz expand the book to include the most recent developments in the field, drawing on nearly a decade of new research as well as their broad clinical wisdom and expertise.New topics include: online therapy, specialized groups, ethnocultural diversity, trauma and managed care. At once scholarly and lively, this is the most up-to-date, incisive, and comprehensive text available on group psychotherapy.

    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.

    The Twelfth Edition's hallmark continues to be its pioneering integration of the proven-effective SQ4R learning system (Survey, Question, Read, Reflect, Review, Recite), which promotes critical thinking as it guides students step-by-step to an understanding of psychology's broad concepts and diversity of topics. Throughout every chapter, these active learning tools—together with the book's example-laced writing style, discussions of positive psychology, cutting-edge coverage of the field's new research findings, and excellent media resources—ensure that students find the study of psychology fascinating, relevant, and above all, accessible.

    Permanent positions are scarce, science survival is rarely part of formal graduate training, and a good mentor is hard to find. This exceptional volume explains what stands between you and fulfilling long-term research career. Bringing the key survival skills into focus, A Ph.D. Is Not Enough! proposes a rational approach to establishing yourself as a scientist. It offers sound advice of selecting a thesis or postdoctoral adviser, choosing among research jobs in academia, government laboratories, and industry, preparing for an employment interview, and defining a research program. This book will help you make your oral presentations effective, your journal articles compelling, and your grant proposals successful. A Ph.D. Is Not Enough should be required reading for anyone on the threshold of a career in science.