The "Logo, Font & Lettering Bible" provides the start-to-finish information you need to succeed in today's competitive design market.

    It's frustrating, and it creates tension. When effective communication is missing in the workplace, employees feel like they're working in the dark. Leaders don't have crucial conversations; managers are frustrated when outcomes are not what they expect; and employees often don’t get positive feedback or constructive feedback. Many of us remain passive against poor communication habits and communication barriers, hoping that business communication will miraculously improve--but it won't. Business communication and relationships won’t improve without skills and effort.The people you work with can work with you, around you, or against you. How people work with you depends on the business relationships you cultivate. Do your colleagues trust you? Can they speak openly to you when projects and tasks go awry? Do you have effective communication skills? Take charge of your career by eliminating communication barriers and taking charge of your business relationships. Make your work environment less tense and more productive by improving communication skills. Set relationship expectations, work with people how they like to work, and give positive feedback and constructive feedback.In How to Say Anything to Anyone, you'll learn how to:- ask for what you want at work- improve communication skills- strengthen all types of working relationships - reduce the gossip and drama in your office - tell people when you’re frustrated and have difficult conversations in a way that resonates - take action on your ideas and feelings- get honest positive feedback and constructive feedback on your performanceHarley shares the real-life stories of people who have struggled to get what they want at work. With her clear and specific business communication roadmap in hand, Harley enables you to improve communication skills and create the career and business relationships you really want--and keep them.

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    Throughout, the emphasis is on promoting a plain English style. This little book can help you communicate more effectively by showing you how to enliven your sentences.

    But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

    The Imagineers are like Santa's elves: they are the nuts-and-bolts workers who allow Disney's magic to take flight. Walt Disney Imagineering explains in colorful detail the making of the magic of Walt Disney World, Disneyland, Disneyland Paris, and Tokyo Disneyland -- the world's most popular vacation "kingdoms" -- from the inside out. From Mickey's Toontown to Blizzard Beach, the wizardry of the Imagineers is brought to life in this book through drawings, models, artwork, and anecdotes; also featured are the now legendary conceptual sketches from Walt Disney's very own pencil. Walt Disney Imagineering is sure to inform and fascinate history buffs, art collectors, graphic designers, architects, engineers, and Disney fans alike.

    What hasn't changed, however, are the basics behind creating a powerful visual - what to say, why to say it, and how to say it for the most impact. In Say It With Charts, Fourth Edition --the latest, cutting-edge edition of his best-selling presentation guide -- Gene Zelazny reveals time-tested tips for preparing effective presentations. Then, this presentation guru shows you how to combine those tips with today's hottest technologies for sharper, stronger visuals. Look to this comprehensive presentation encyclopedia for information on:* How to prepare different types of charts -- pie, bar, column, line, or dot -- and when to use each * Lettering size, color choice, appropriate chart types, and more * Techniques for producing dramatic eVisuals using animation, scanned images, sound, video, and links to pertinent websites

    But as architect William McDonough and chemist Michael Braungart point out in this provocative, visionary book, such an approach only perpetuates the one-way, "cradle to grave" manufacturing model, dating to the Industrial Revolution, that creates such fantastic amounts of waste and pollution in the first place. Why not challenge the belief that human industry must damage the natural world? In fact, why not take nature itself as our model for making things? A tree produces thousands of blossoms in order to create another tree, yet we consider its abundance not wasteful but safe, beautiful, and highly effective.Waste equals food. Guided by this principle, McDonough and Braungart explain how products can be designed from the outset so that, after their useful lives, they will provide nourishment for something new. They can be conceived as "biological nutrients" that will easily reenter the water or soil without depositing synthetic materials and toxins. Or they can be "technical nutrients" that will continually circulate as pure and valuable materials within closed-loop industrial cycles, rather than being "recycled" -- really, downcycled -- into low-grade materials and uses. Drawing on their experience in (re)designing everything from carpeting to corporate campuses, McDonough and Braungart make an exciting and viable case for putting eco-effectiveness into practice, and show how anyone involved with making anything can begin to do as well.

    First published in English in 1995, with an excellent introduction by Robin Kinross, this new edition includes a foreword by Rich Hendel, who considers current thinking about Tschichold's life and work.

    This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

    This special 25th anniversary edition of Tattoos explores the history of the art worldwide via designs and photos—from 19th century engravings to tribal body art, from circus ladies of the 20s to classic biker designs—giving a fascinating insight into the art of tattooing.

    You’ll begin at square one, learning how the Web and web pages work, and then steadily build from there. By the end of the book, you’ll have the skills to create a simple site with multi-column pages that adapt for mobile devices.Learn how to use the latest techniques, best practices, and current web standards—including HTML5 and CSS3. Each chapter provides exercises to help you to learn various techniques, and short quizzes to make sure you understand key concepts.This thoroughly revised edition is ideal for students and professionals of all backgrounds and skill levels, whether you’re a beginner or brushing up on existing skills.Build HTML pages with text, links, images, tables, and formsUse style sheets (CSS) for colors, backgrounds, formatting text, page layout, and even simple animation effectsLearn about the new HTML5 elements, APIs, and CSS3 properties that are changing what you can do with web pagesMake your pages display well on mobile devices by creating a responsive web designLearn how JavaScript works—and why the language is so important in web designCreate and optimize web graphics so they’ll download as quickly as possible