This Missing Manual shows you how to take your HTML and CSS skills to the next level, with valuable tips, tricks, and step-by-step instructions. You’ll quickly learn how to build web pages that look great and run fast on devices and screens of all sizes.The important stuff you need to know:Start with the basics. Write CSS3-friendly HTML, including the HTML5 tags recognized by today’s browsers.Apply real-world design. Format text, create navigation tools, and enhance pages with graphics.Make your pages lively. Create eye-catching animations and give your visitors attractive tables and forms.Take control of page layouts. Use professional design techniques such as floats and positioning.Look great on any device. Craft websites that adapt to desktop, tablet, and mobile browsers.Get advanced techniques. Use CSS3 more effectively and efficiently, and ensure that your web pages look good when printed.

    In the wake of his death WIRED presents Steve Jobs: Revolutionary, an eBook featuring our best stories about him. The anthology begins with a remembrance by Wired senior writer Steven Levy, who interviewed Jobs many times over the last two decades. We continue with six other stories that track Jobs on his uncanny rise, his dramatic fall, and his spectacular, unlikely return to Apple.

    Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks.Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data--or anything in between--this guide makes it easier to understand and implement machine learning seamlessly.Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!

    In a world saturated with marketing messages, making your offering relevant is your biggest challenge. Dentsu's Cross Switch model meets it head on.The Dentsu Way shares proven tactics for getting your message to consumers and creating scenarios to move them through calibrated Contact Points to meet whatever specific goal you set.This game-changing book:Explains Dentsu's 110-year history and unique service structure, as well as its broad range of business fieldsIntroduces ten case studies of successful campaigns, which have won international advertising awards at events such as the Cannes Lions International Advertising Festival and ADFESTProvides nine of Dentsu's newest original tools and analysis methodsGain broader, more meaningful customer involvement and penetrate more deeply than ever into your market by following the Dentsu Way.

    Its broad appeal lies in its interactive environment with hundreds of built-in functions for technical computation, graphics, and animation. In addition, it provides easy extensibility with its own high-level programming language. Enhanced by fun and appealing illustrations, Getting Started with MATLAB 7: A Quick Introduction for Scientists and Engineers employs a casual, accessible writing style that shows users how to enjoy using MATLAB.

    Essentially, you are estimating a probability, but then updating that estimate based on other things that you know. This book is designed to give you an intuitive understanding of how to use Bayes Theorem. It starts with the definition of what Bayes Theorem is, but the focus of the book is on providing examples that you can follow and duplicate. Most of the examples are calculated in Excel, which is useful for updating probability if you have dozens or hundreds of data points to roll in.

    With this guide, pioneering Go programmer Mark Summerfield shows how to write code that takes full advantage of Go's breakthrough features and idioms. Both a tutorial and a language reference, "Programming in Go" brings together all the knowledge you need to evaluate Go, think in Go, and write high-performance software with Go. Summerfield presents multiple idiom comparisons showing exactly how Go improves upon older languages, calling special attention to Go's key innovations. Along the way, he explains everything from the absolute basics through Go's lock-free channel-based concurrency and its flexible and unusual duck-typing type-safe approach to object-orientation. Throughout, Summerfield's approach is thoroughly practical. Each chapter offers multiple live code examples designed to encourage experimentation and help you quickly develop mastery. Wherever possible, complete programs and packages are presented to provide realistic use cases, as well as exercises. Coverage includes:-- Quickly getting and installing Go, and building and running Go programs -- Exploring Go's syntax, features, and extensive standard library -- Programming Boolean values, expressions, and numeric types -- Creating, comparing, indexing, slicing, and formatting strings -- Understanding Go's highly efficient built-in collection types: slices and maps -- Using Go as a procedural programming language -- Discovering Go's unusual and flexible approach to object orientation -- Mastering Go's unique, simple, and natural approach to fine-grained concurrency -- Reading and writing binary, text, JSON, and XML files -- Importing and using standard library packages, custom packages, and third-party packages -- Creating, documenting, unit testing, and benchmarking custom packages

    Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.