Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Persistence theory emerged in the early 2000s as a new theory in the area of applied and computational topology. This book provides a broad and modern view of the subject, including its algebraic, topological, and algorithmic aspects. It also elaborates on applications in data analysis. The level of detail of the exposition has been set so as to keep a survey style, while providing sufficient insights into the proofs so the reader can understand the mechanisms at work. The book is organized into three parts. The first part is dedicated to the foundations of persistence and emphasizes its connection to quiver representation theory. The second part focuses on its connection to applications through a few selected topics. The third part provides perspectives for both the theory and its applications. The book can be used as a text for a course on applied topology or data analysis.

Legendary leadership and elite performance expert Robin Sharma introduced The 5am Club concept over twenty years ago, based on a revolutionary morning routine that has helped his clients maximize their productivity, activate their best health and bulletproof their serenity in this age of overwhelming complexity. Now, in this life-changing book, handcrafted by the author over a rigorous four-year period, you will discover the early-rising habit that has helped so many accomplish epic results while upgrading their happiness, helpfulness and feelings of aliveness. Through an enchanting—and often amusing—story about two struggling strangers who meet an eccentric tycoon who becomes their secret mentor, The 5am Club will walk you through: How great geniuses, business titans and the world’s wisest people start their mornings to produce astonishing achievements A little-known formula you can use instantly to wake up early feeling inspired, focused and flooded with a fiery drive to get the most out of each day A step-by-step method to protect the quietest hours of daybreak so you have time for exercise, self-renewal and personal growth A neuroscience-based practice proven to help make it easy to rise while most people are sleeping, giving you precious time for yourself to think, express your creativity and begin the day peacefully instead of being rushed “Insider-only” tactics to defend your gifts, talents and dreams against digital distraction and trivial diversions so you enjoy fortune, influence and a magnificent impact on the world Part manifesto for mastery, part playbook for genius-grade productivity and part companion for a life lived beautifully, The 5am Club is a work that will transform your life. Forever.

The forms taken by scientific writing help to determine the very nature of science itself. In this closely reasoned study, Charles Bazerman views the changing forms of scientific writing as solutions to rhetorical problems faced by scientists arguing for their findings. Examining such works as the early Philosophical Transactions and Newton's optical writings as well as Physical Review, Bazerman views the changing forms of scientific writing as solutions to rhetorical problems faced by scientists. The rhetoric of science is, Bazerman demonstrates, an embedded part of scientific activity that interacts with other parts of scientific activity, including social structure and empirical experience. This book presents a comprehensive historical account of the rise and development of the genre, and views these forms in relation to empirical experience.

In 1937 Ernest Hemingway traveled to Spain to cover the civil war there for the North American Newspaper Alliance. Three years later he completed the greatest novel to emerge from “the good fight,” For Whom the Bell Tolls. The story of Robert Jordan, a young American in the International Brigades attached to an antifascist guerilla unit in the mountains of Spain, it tells of loyalty and courage, love and defeat, and the tragic death of an ideal. In his portrayal of Jordan's love for the beautiful Maria and his superb account of El Sordo's last stand, in his brilliant travesty of La Pasionaria and his unwillingness to believe in blind faith, Hemingway surpasses his achievement in The Sun Also Rises and A Farewell to Arms to create a work at once rare and beautiful, strong and brutal, compassionate, moving, and wise. “If the function of a writer is to reveal reality,” Maxwell Perkins wrote to Hemingway after reading the manuscript, “no one ever so completely performed it.” Greater in power, broader in scope, and more intensely emotional than any of the author's previous works, it stands as one of the best war novels of all time.

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. 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 Resource The 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.

Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect