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

    Written in a clear and accessible narrative, the 7th Edition focuses on fundamental principles and their applications to solving real circuit analysis problems, and devotes six chapters to examining electronic devices. With an eye-catching visual program and practical exercises, this book provides readers with the problem-solving experience they need in a style that makes complex material thoroughly understandable. For professionals with a career in electronics, engineering, technical sales, field service, industrial manufacturing, service shop repair, and/or technical writing.

    Purchase includes a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: A Short History of Nearly Everything, the Life and Times of the Thunderbolt Kid, a Walk in the Woods, Notes From a Small Island, Neither Here nor There: Travels in Europe, Shakespeare: the World as Stage, the Lost Continent: Travels in Small-Town America, the Mother Tongue, Notes From a Big Country, Bryson's Dictionary of Troublesome Words, Down Under, Made in America, Bill Bryson's African Diary. Source: Wikipedia. Free updates online. Not illustrated. Excerpt: A Short History of Nearly Everything (ISBN 0-7679-0817-1) is a general science book by Bill Bryson, which explains some areas of science, using a style of language more accessible to the general public than many other books dedicated to the subject. It was the bestselling popular science book of 2005 in the UK, selling over 300,000 copies. A Short History deviates from Bryson's popular travel book genre, instead describing general sciences such as chemistry, paleontology, astronomy, and particle physics. In it, he explores time from the Big Bang to the discovery of quantum mechanics, via evolution and geology. Bryson tells the story of science through the stories of the people who made the discoveries, such as Edwin Hubble, Isaac Newton, and Albert Einstein. Bill Bryson wrote this book because he was dissatisfied with his scientific knowledge that was, not much at all. He writes that science was a distant, unexplained subject at school. Textbooks and teachers alike did not ignite the passion for knowledge in him, mainly because they never delved in the whys, hows, and whens. "It was as if wanted to keep the good stuff secret by making all of it soberly unfathomable." Bryson, on the state of science books used within his school. It was in his later years that he realized with stunning shame ...More: http: //booksllc.net/?id=101240

    During World War I, the young women who were hired to work in America's radium watch dial factories were considered the lucky ones. They were paid well, they got to work with the luminous element dubbed "liquid sunshine" that was all the rage, and they were helping the war effort by providing instruments that shone in the dark. And their bodies literally glowed because of the amount of radium they were ingesting. In her new book, The Radium Girls: The Dark Story of America's Shining Women, author Kate Moore gives voice to two groups of workers who became horribly ill and fought back against the companies that poisoned them. Using diaries and letters from the women, their statements in court documents, medical records and archived x-rays, as well as using ancestry documents to track down their relatives for interviews, Moore showcases the forgotten young women whose legal fight led to life-changing workplace safety regulations amid one of the biggest scandals of America's twentieth century. Preorder and find out how their story ends on May 2.

     This book is perfect for history lovers. Author James Weber did the research and compiled this huge list of events that changed the course of history forever. Some of them include: - The first civilization in Mesopotamia in 3,000 B.C. - The Norman Invasion of England in 1066 - The invention of the printing press by Johannes Guttenberg around 1450 - The French Revolution in 1789 - The first motorized airplane flight in 1903 - The Moonlanding in 1969 and many many more The book includes pictures and explanations to every event, making this the perfect resource for students and anyone wanting to broaden their knowledge in histoy. Download your copy now! Tags: history, world history, history books, history of the world, human history, world history textbook, history books for kids, earth history, geographic history, earth history kindle, human history, history books for kids age 9 12, history of the world part 1, a little history of the world, history books for kids age 7-9, history books for young readers, history books for children, history books for kindle,

    

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    In this book, Agile Alliance cofounder Mike Cohn discusses the philosophy of agile estimating and planning and shows you exactly how to get the job done, with real-world examples and case studies.Concepts are clearly illustrated and readers are guided, step by step, toward how to answer the following questions: What will we build? How big will it be? When must it be done? How much can I really complete by then? You will first learn what makes a good plan-and then what makes it agile.Using the techniques in Agile Estimating and Planning , you can stay agile from start to finish, saving time, conserving resources, and accomplishing more. Highlights include:Why conventional prescriptive planning fails and why agile planning works How to estimate feature size using story points and ideal days--and when to use each How and when to re-estimate How to prioritize features using both financial and nonfinancial approaches How to split large features into smaller, more manageable ones How to plan iterations and predict your team's initial rate of progress How to schedule projects that have unusually high uncertainty or schedule-related risk How to estimate projects that will be worked on by multiple teams Agile Estimating and Planning supports any agile, semiagile, or iterative process, including Scrum, XP, Feature-Driven Development, Crystal, Adaptive Software Development, DSDM, Unified Process, and many more. It will be an indispensable resource for every development manager, team leader, and team member.

    He decried the internment of Japanese-Americans in World War Two, agitated against nuclear weapons, promoted vitamin C as a cure for the common cold and researched the idea of DNA.

    Verification that algorithms work is emphasized more than their complexity. An effective use of examples, and huge number of interesting exercises, demonstrate the topics of trees and distance, matchings and factors, connectivity and paths, graph coloring, edges and cycles, and planar graphs. For those who need to learn to make coherent arguments in the fields of mathematics and computer science.

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer's memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R's package system and debugging toolsPractice and apply R programming concepts as you learn them

    We start off easy, defining some of the tech lingo you may have heard before, but didn’t fully understand. From there, each lesson introduces something new, slowly building up to the point where you are confident about what an API is and, for the brave, could actually take a stab at using one.

    This staggering amount of information—unprecedented in history—can tell us a great deal about who we are—the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than twenty years ago, seemed unfathomable.Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women?Investigating these questions and a host of others, Seth Stephens-Davidowitz offers revelations that can help us understand ourselves and our lives better. Drawing on studies and experiments on how we really live and think, he demonstrates in fascinating and often funny ways the extent to which all the world is indeed a lab. With conclusions ranging from strange-but-true to thought-provoking to disturbing, he explores the power of this digital truth serum and its deeper potential—revealing biases deeply embedded within us, information we can use to change our culture, and the questions we’re afraid to ask that might be essential to our health—both emotional and physical. All of us are touched by big data everyday, and its influence is multiplying. Everybody Lies challenges us to think differently about how we see it and the world.

    They were the rank underdogs and they swept to victory on an unprecedented tide of goodwill that washed over the nation. Only Martin Flanagan could bring to life this particular miracle. The club's two guiding spirits - captain Bob Murphy and coach Luke Beveridge - welcomed him in, Beveridge making available his match diaries, pre-match notes and video highlights. Flanagan interviewed every player, watched every match, talked with the trainers, the women in the football department, the fans who never miss a training session, the cheer squad.What Flanagan shows is that the Bulldogs found a new way to play partly because they found a new way to be a team - a new way to support each other, even a new way to be. A Wink from the Universe takes us into the heart of the community Luke Beveridge and Bob Murphy dreamt into being with the support of the Bulldog people around them. This is a classic of sportswriting - a book for fans of the club, and of the game, but also a book for anyone who wants to know how a group of people can will a miracle to happen.