Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    The linear metaphor is ubiquitous in everyday visual representations of time—in almanacs, calendars, charts, and graphs of all sorts. Even our everyday speech is filled with talk of time having a "before" and an "after" or being "long" and "short." The timeline is such a familiar part of our mental furniture that it is sometimes hard to remember that we invented it in the first place. And yet, in its modern form, the timeline is not even 250 years old. The story of what came before has never been fully told, until now. Cartographies of Time is the first comprehensive history of graphic representations of time in Europe and the United States from 1450 to the present. Authors Daniel Rosenberg and Anthony Grafton have crafted a lively history featuring fanciful characters and unexpected twists and turns. From medieval manuscripts to websites, Cartographies of Time features a wide variety of timelines that in their own unique ways—curving, crossing, branching—defy conventional thinking about the form. A fifty-four-foot-long timeline from 1753 is mounted on a scroll and encased in a protective box. Another timeline uses the different parts of the human body to show the genealogies of Jesus Christ and the rulers of Saxony. Ladders created by missionaries in eighteenth-century Oregon illustrate Bible stories in a vertical format to convert Native Americans. Also included is the April 1912 Marconi North Atlantic Communication chart, which tracked ships, including the Titanic, at points in time rather than by theirgeographic location, alongside little-known works by famous figures, including a historical chronology by the mapmaker Gerardus Mercator and a chronological board game patented by Mark Twain. Presented in a lavishly illustrated edition, Cartographies of Time is a revelation to anyone interested in the role visual forms have played in our evolving conception of history.

    Redesigning your home page won't help. Investing in a new content management system won't fix it, either. So, where do you start? Without meaningful content, your website isn't worth much to your key audiences. But creating (and caring for) "meaningful" content is far more complicated than we're often willing to acknowledge. Content Strategy for the Web explains how to create and deliver useful, usable content for your online audiences, when and where they need it most. It also shares content best practices so you can get your next website redesign right, on time and on budget. For the first time, you'll: See content strategy (and its business value) explained in plain languageFind out why so many web projects implode in the content development phase ... and how to avoid the associated, unnecessary costs and delaysLearn how to audit and analyze your contentMake smarter, achievable decisions about which content to create and howFind out how to maintain consistent, accurate, compelling content over timeGet solid, practical advice on staffing for content-related roles and responsibilities "

    R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you'll need to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You'll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you're done, you won't just know how to write R programs, you'll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES - Exploring R, RStudio, and R packages - Using R for math: variable types, vectors, calling functions, and more - Exploiting data structures, including data.frames, matrices, and lists - Creating attractive, intuitive statistical graphics - Writing user-defined functions - Controlling program flow with if, ifelse, and complex checks - Improving program efficiency with group manipulations - Combining and reshaping multiple datasets - Manipulating strings using R's facilities and regular expressions - Creating normal, binomial, and Poisson probability distributions - Programming basic statistics: mean, standard deviation, and t-tests - Building linear, generalized linear, and nonlinear models - Assessing the quality of models and variable selection - Preventing overfitting, using the Elastic Net and Bayesian methods - Analyzing univariate and multivariate time series data - Grouping data via K-means and hierarchical clustering - Preparing reports, slideshows, and web pages with knitr - Building reusable R packages with devtools and Rcpp - Getting involved with the R global community

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    Everyone can ask questions, right? Unfortunately, that's not the case. Interviewing Users provides invaluable interviewing techniques and tools that enable you to conduct informative interviews with anyone. You'll move from simply gathering data to uncovering powerful insights about people.Interviewing Users will explain how to succeed with interviewing, including:* Embracing how other people see the world* Building rapport to create engaging and exciting interactions* Listening in order to build rapport.With this book, Steve Portigal uses stories and examples from his 15 years of experience to show how interviewing can be incorporated into the design process, helping you learn the best and right information to inform and inspire your design.

    With this practical book, you'll explore the often-misunderstood practice of user story mapping, and learn how it can help keep your team stay focused on users and their experience throughout the development process.You and your team will learn that user stories aren't a way to write better specifications, but a way to organize and have better conversations. This book will help you understand what kinds of conversations you should be having, when to have them, and what to keep track of when you do. Learn the key concepts used to create a great story map. Understand how user stories really work, and how to make good use of them in agile and lean projects. Examine the nuts and bolts of managing stories through the development cycle. Use strategies that help you continue to learn before and after the product's release to customers and usersUser Story Mapping is ideal for agile and lean software development team members, product managers and UX practitioners in commercial product companies, and business analysts and project managers in IT organizations—whether you're new to this approach or want to understand more about it.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    Drawing heavily on the author's own real-world experiences, the book stresses design and analysis. Coverage is divided into two parts, the first being a general guide to techniques for the design and analysis of computer algorithms. The second is a reference section, which includes a catalog of the 75 most important algorithmic problems. By browsing this catalog, readers can quickly identify what the problem they have encountered is called, what is known about it, and how they should proceed if they need to solve it. This book is ideal for the working professional who uses algorithms on a daily basis and has need for a handy reference. This work can also readily be used in an upper-division course or as a student reference guide. THE ALGORITHM DESIGN MANUAL comes with a CD-ROM that contains: * a complete hypertext version of the full printed book. * the source code and URLs for all cited implementations. * over 30 hours of audio lectures on the design and analysis of algorithms are provided, all keyed to on-line lecture notes.

    Management is a key part of any organization, yet the discipline is often self-taught and unstructured. Getting to the good solutions of complex management challenges can make the difference between fulfillment and frustration for teams, and, ultimately, the success or failure of companies. Will Larson's An Elegant Puzzle orients around the particular challenges of engineering management--from sizing teams to technical debt to succession planning--and provides a path to the good solutions. Drawing from his experience at Digg, Uber, and Stripe, Will Larson has developed a thoughtful approach to engineering management that leaders of all levels at companies of all sizes can apply. An Elegant Puzzle balances structured principles and human-centric thinking to help any leader create more effective and rewarding organizations for engineers to thrive in.

    You’ll learn…• How a noise reduction headset at 35,000 feet led to the creation of Pepsi’s new trademarked signature sound.• How a worn down sneaker discovered in the home of an 11-year-old German boy led to LEGO’s incredible turnaround.• How a magnet found on a fridge in Siberia resulted in a U.S. supermarket revolution.• How a toy stuffed bear in a girl’s bedroom helped revolutionize a fashion retailer’s 1,000 stores in 20 different countries.• How an ordinary bracelet helped Jenny Craig increase customer loyalty by 159% in less than a year.• How the ergonomic layout of a car dashboard led to the redesign of the Roomba vacuum.

    And now there’s a sure-fire way to solve their problems and test solutions: the sprint.While working at Google, designer Jake Knapp created a unique problem-solving method that he coined a “design sprint”—a five-day process to help companies answer crucial questions. His ‘sprints’ were used on everything from Google Search to Chrome to Google X. When he moved to Google Ventures, he joined Braden Kowitz and John Zeratsky, both designers and partners there who worked on products like YouTube and Gmail. Together Knapp, Zeratsky, and Kowitz have run over 100 sprints with their portfolio companies. They’ve seen firsthand how sprints can overcome challenges in all kinds of companies: healthcare, fitness, finance, retailers, and more.A practical guide to answering business questions, Sprint is a book for groups of any size, from small startups to Fortune 100s, from teachers to non-profits. It’s for anyone with a big opportunity, problem, or idea who needs to get answers today.

    This book aims to minimize the complexity of user-centered design for the Web with explanations and illustrations that focus on ideas rather than tools or techniques.

     Universal Methods of Design serves as an invaluable compendium of methods that can be easily referenced and used by cross-disciplinary teams in nearly any design project.   Methods and techniques are organized alphabetically for ongoing, quick reference. Each method is presented in a two-page format. The left-hand page contains a concise description of the method, accompanied by references for further reading. On the right-hand page, images and cases studies for each method are presented visually. The relevant phases for design application are highlighted as numbered icons along the right side of the page, from phases 1 (planning) through 5 (launch and monitor).Build more meaningful products with these methods and more: A/B Testing, Affinity Diagramming, Behavioral Mapping, Bodystorming, Contextual Design, Critical Incident Technique, Directed Storytelling, Flexible Modeling, Image Boards, Graffiti Walls, Heuristic Evaluation, Parallel Prototyping, Simulation Exercises, Touchstone Tours, and Weighted Matrix.  This essential guide:Dismantles the myth that user research methods are complicated, expensive, and time-consumingCreates a shared meaning for cross-disciplinary design teamsIllustrates methods with compelling visualizations and case studiesCharacterizes each method at a glanceIndicates when methods are best employed to help prioritize appropriate design research strategiesUniversal Methods of Design is an essential resource for designers of all levels and specializations.