“Tell him all weren’t lost in the Cardamom Mountains,” he says and is suddenly gone, swept up in a swirling eddy of rain and leaves. The message is intended for both Sheriff John Ryan and Father Santos. It prompts the two, along with Mia and Murphy, to return to the place they first met, Cambodia.Meanwhile, the Big Bear Lake Cemetery is vandalized, and bodies are found to be missing from the Weller mausoleum. To make matters worse, the deputy in charge of the investigation quickly becomes missing too. Acting-Sheriff Tom Braverman deputizes Ted, Cid and Ed to find his deputy. What dangerous game are these spirits playing with both the living and the dead?Mia has avoided the corrupted ground of the Big Bear Lake Cemetery all her life since she was found screaming at the crossroads of the graveyard when she was a young child. She tries to stay out of this investigation, but there is another restless spirit there who will only deal with her. This brings her back to the graveyard to face her greatest fear, in a fight that she may not win. Will her nemesis claim her, or will Mia survive another encounter with the Countess?Come and join Mia, Murphy, PEEPs, and friends as they navigate through the supernatural and the paranormal worlds to discover what “The Long Game” has been all along. Who are the players, and who are the pieces? And who will survive the game?“The Long Game” is the 19th novel of the “Haunted Series.”

    

    . . like a pendulum? These may not look like math questions, but they are-because they all have to do with patterns. And mathematics, at heart, is the study of patterns. That realization changed Eddie Woo's life-by turning the "dry" subject he dreaded in high school into a boundless quest for discovery. Now an award-winning math teacher, Woo sees patterns everywhere: in the "branches" of blood vessels and lightning, in the growth of a savings account and a sunflower, even in his morning cup of tea! Here are twenty-six bite-size chapters on the hidden mathematical marvels that encrypt our email, enchant our senses, and even keep us alive-from the sine waves we hear as "music" to the mysterious golden ratio. This book will change your mind about what math can be. We are all born mathematicians-and It's a Numberful World.

    You’ll learn principles and practices for crafting games that generate emotionally charged experiences—a combination of elegant game mechanics, compelling fiction, and pace that fully immerses players.In clear and approachable prose, design pro Tynan Sylvester also looks at the day-to-day process necessary to keep your project on track, including how to work with a team, and how to avoid creative dead ends. Packed with examples, this book will change your perception of game design.Create game mechanics to trigger a range of emotions and provide a variety of playExplore several options for combining narrative with interactivityBuild interactions that let multiplayer gamers get into each other’s headsMotivate players through rewards that align with the rest of the gameEstablish a metaphor vocabulary to help players learn which design aspects are game mechanicsPlan, test, and analyze your design through iteration rather than deciding everything up frontLearn how your game’s market positioning will affect your design

    One of the first such volumes designed specifically as a textbook,it differs from the strictly professional robotics book in its use of learning aids. Example problems,case studies,and end-of-chapter exercises serve to reinforce important concepts.

    The book has three parts: Principles: Part one covers the leadership principles that PMs use to lead their team to overcome adversity. When your product fails to gain traction, when your team falls apart, or when your manager gives you tough feedback—these are all opportunities to learn principles that will help you succeed. Product development: Part two covers how PMs at Facebook, Amazon, and other top companies build products. We'll walk through the end-to-end product development process— from understanding the customer problem to identifying the right product to build to executing with your team to bring the product to market. Getting the job: Part three covers how you can land a PM job and reach the interview stage at the right company. We'll prep you for the three most common types of PM interviews— product sense, execution, and behavioral—with detailed frameworks and examples for each. Hear directly from product leaders at Airbnb, Amazon, Google, and more on: How to overcome challenging situations from a VP of Product at Amazon. How to build a great product roadmap from product leaders at LinkedIn and Airbnb. How Google, Airbnb, and other top companies evaluate PM candidates from leaders at those companies. How PMs can grow their career from a Director at Instagram and Twitter. Table of Contents1. PrinciplesTake OwnershipPrioritize and ExecuteStart with WhyFind the TruthBe Radically TransparentBe Honest with Yourself2. Product DevelopmentProduct Development LoopUnderstanding the Customer ProblemSelecting a Goal MetricMission, Vision, and StrategyBuilding a Product RoadmapDefining Product RequirementsGreat Project ManagementEffective CommunicationMaking Good Decisions3. Getting the JobPreparing for the TransitionMaking the TransitionFinding the Right CompanyAcing your PM InterviewsProduct Sense InterviewExecution InterviewBehavioral InterviewYour First 30 Days4. Product Leader Interviews

    Sold in over 85 countries and translated into more than 5 languages.---------------Want to get started on data science?Our promise: no math added.This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations and visuals.Popular concepts covered include:- A/B Testing- Anomaly Detection- Association Rules- Clustering- Decision Trees and Random Forests- Regression Analysis- Social Network Analysis- Neural NetworksFeatures:- Intuitive explanations and visuals- Real-world applications to illustrate each algorithm- Point summaries at the end of each chapter- Reference sheets comparing the pros and cons of algorithms- Glossary list of commonly-used termsWith this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions.

    Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a “Feynmanesque” overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.

    This book provides the design strategy and tactics you need to integrate game mechanics into any kind of consumer-facing website or mobile app. Learn how to use core game concepts, design patterns, and meaningful code samples to a create fun and captivating social environment.Whether you're an executive, developer, producer, or product specialist, Gamification by Design will show you how game mechanics can help you build customer loyalty.Discover the motivational framework game designers use to segment and engage consumersUnderstand core game mechanics such as points, badges, levels, challenges, and leaderboardsEngage your consumers with reward structures, positive reinforcement, and feedback loopsCombine game mechanics with social interaction for activities such as collecting, gifting, heroism, and statusDive into case studies on Nike and Yahoo!, and analyze interactions at Google, Facebook, and ZyngaGet the architecture and code to gamify a basic consumer site, and learn how to use mainstream gamification APIs from Badgeville"Turning applications into games is a huge trend. This book does a great job of identifying the core lasting principals you need to inspire your users to visit again and again." —Adam Loving Freelance Social Game Developer and founder of Twibes Twitter Groups

    It describes how the laws and discoveries of information theory now support controversial revisions to Darwinian evolution, begin to unravel the mysteries of language, memory and dreams, and stimulate provocative ideas in psychology, philosophy, art, music, computers and even the structure of society. Perhaps its most fascinating and unexpected surprise is the suggestion the order and complexity may be as natural as disorder and disorganization. Contrary to the entropy principle, which implies that order is the exception and confusion the rule, information theory asserts that order and sense can indeed prevail against disorder and nonsense. From the simplest forms of organic life to the words used to express our most complex ideas, from our genes to our dreams, from microcomputers to telecommunications, virtually everything around us follows simple rules of information. Life and the material world, like language, remain "grammatical." Grammatical man inhabits a grammatical universe.

    The author has sought to utlilize the technology now available for the teaching and learning of calculus. The hand-held graphics calculator is one such form of technology that has been integrated into the book. Topics in algebra, trigonometry, and analytical geometry appear in the Appendix.

    And then we wonder why software is notorious for being delivered late and full of bugs, while other engineers routinely deliver finished bridges, automobiles, electrical appliances, etc., on time and with only minor defects. This book sets out to redress this imbalance. Members of my advanced development team at Adobe who took the course based on the same material all benefited greatly from the time invested. It may appear as a highly technical text intended only for computer scientists, but it should be required reading for all practicing software engineers." --Martin Newell, Adobe Fellow"The book contains some of the most beautiful code I have ever seen." --Bjarne Stroustrup, Designer of C++"I am happy to see the content of Alex's course, the development and teaching of which I strongly supported as the CTO of Silicon Graphics, now available to all programmers in this elegant little book." --Forest Baskett, General Partner, New Enterprise Associates"Paul's patience and architectural experience helped to organize Alex's mathematical approach into a tightly-structured edifice--an impressive feat!" --Robert W. Taylor, Founder of Xerox PARC CSL and DEC Systems Research Center Elements of Programming provides a different understanding of programming than is presented elsewhere. Its major premise is that practical programming, like other areas of science and engineering, must be based on a solid mathematical foundation. The book shows that algorithms implemented in a real programming language, such as C++, can operate in the most general mathematical setting. For example, the fast exponentiation algorithm is defined to work with any associative operation. Using abstract algorithms leads to efficient, reliable, secure, and economical software.This is not an easy book. Nor is it a compilation of tips and tricks for incremental improvements in your programming skills. The book's value is more fundamental and, ultimately, more critical for insight into programming. To benefit fully, you will need to work through it from beginning to end, reading the code, proving the lemmas, and doing the exercises. When finished, you will see how the application of the deductive method to your programs assures that your system's software components will work together and behave as they must.The book presents a number of algorithms and requirements for types on which they are defined. The code for these descriptions--also available on the Web--is written in a small subset of C++ meant to be accessible to any experienced programmer. This subset is defined in a special language appendix coauthored by Sean Parent and Bjarne Stroustrup.Whether you are a software developer, or any other professional for whom programming is an important activity, or a committed student, you will come to understand what the book's experienced authors have been teaching and demonstrating for years--that mathematics is good for programming, and that theory is good for practice.

    The mathematician, born on June 23, 1912, was a brilliant World War II codebreaker and parlayed that insight into theorizing and creating the first stored-memory computers. Unfortunately, this Officer of the British Empire was persecuted by the British government of the time for his homosexuality and suffered through chemical castration before ending his life.The Imitation Game by Feynman author Jim Ottaviani and Resistance illustrator Leland Purvis chronicles the life of Turing in a full-size graphic novel. Available online at http://www.tor.com/stories/2014/06/th...

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    And if every page of these chapters does not proclaim to the reader that the only means for the realization of Truth is ahimsa, I shall deem all my labour in writing these chapters to have been in vain. And, even though my efforts in this behalf may prove fruitless, let the readers know that the vehicle, not the great principle, is at fault.- M. K. Gandhi