Its second edition, published in 1986, has confirmed that vocabulary is best taught by root, not rote. The importance of learning classical word roots is already acknowledged by vocabulary texts that devote chapters to them. Why a whole book based on this approach? Ayers' text exposes students to a wider range of roots, introduces new English words in context sentences, and reinforces vocabulary through exercises. It promotes more practice with roots so that students learn to use them as tools in their everyday encounters with new words. English Words is written from the standpoint of English; it neither attempts to teach students Latin or Greek nor expects a knowledge of classical languages on the part of instructors. Its success has been demonstrated at both the secondary and college levels, and it can be used effectively with students in remedial or accelerated programs. An Instructor's Manual (gratis with adoption) and a Workbook are also available.

    This authoritative book scrapes away these bad features to reveal a subset of JavaScript that's more reliable, readable, and maintainable than the language as a whole--a subset you can use to create truly extensible and efficient code.Considered the JavaScript expert by many people in the development community, author Douglas Crockford identifies the abundance of good ideas that make JavaScript an outstanding object-oriented programming language-ideas such as functions, loose typing, dynamic objects, and an expressive object literal notation. Unfortunately, these good ideas are mixed in with bad and downright awful ideas, like a programming model based on global variables.When Java applets failed, JavaScript became the language of the Web by default, making its popularity almost completely independent of its qualities as a programming language. In JavaScript: The Good Parts, Crockford finally digs through the steaming pile of good intentions and blunders to give you a detailed look at all the genuinely elegant parts of JavaScript, including:SyntaxObjectsFunctionsInheritanceArraysRegular expressionsMethodsStyleBeautiful featuresThe real beauty? As you move ahead with the subset of JavaScript that this book presents, you'll also sidestep the need to unlearn all the bad parts. Of course, if you want to find out more about the bad parts and how to use them badly, simply consult any other JavaScript book.With JavaScript: The Good Parts, you'll discover a beautiful, elegant, lightweight and highly expressive language that lets you create effective code, whether you're managing object libraries or just trying to get Ajax to run fast. If you develop sites or applications for the Web, this book is an absolute must.

    A logical, expert, easy-to-use plan for achieving excellence in expression, Style offers neither simplistic rules nor endless lists of dos and don'ts. Rather, Joseph Williams explains how to be concise, how to be focused, how to be organized. Filled with realistic examples of good, bad, and better writing, and step-by-step strategies for crafting a sentence or organizing a paragraph, Style does much more than teach mechanics: it helps anyone who must write clearly and persuasively transform even the roughest of drafts into a polished work of clarity, coherence, impact, and personality."Buy Williams's book. And dig out from storage your dog-eared old copy of The Elements of Style. Set them side by side on your reference shelf."—Barbara Walraff, Atlantic"Let newcoming writers discover this, and let their teachers and readers rejoice. It is a practical, disciplined text that is also a pleasure to read."—Christian Century"An excellent book....It provides a sensible, well-balanced approach, featuring prescriptions that work."—Donald Karzenski, Journal of Business Communication"Intensive fitness training for the expressive mind."—Booklist(The college textbook version, Style: Ten Lessons in Clarity and Grace, 9th edition, is available from Longman. ISBN 9780321479358.)

    This book can make you smarter.Mind Performance Hacks provides real-life tips and tools for overclocking your brain and becoming a better thinker. In the increasingly frenetic pace of today's information economy, managing your life requires hacking your brain. With this book, you'll cut through the clutter and tune up your brain intentionally, safely, and productively.Grounded in current research and theory, but offering practical solutions you can apply immediately, Mind Performance Hacks is filled with life hacks that teach you to:Use mnemonic tricks to remember numbers, names, dates, and other flotsam you need to recall. Put down your calculator and perform complex math in your head, with your fingers, or on the back of a napkin. Spark your creativity with innovative brainstorming methods. Use effective systems to capture new ideas before they get away. Communicate in creative new ways-even using artificial languages. Make better decisions by foreseeing problems and finding surprising solutions. Improve your mental fitness with cool tricks and games.While the hugely successful Mind Hacks showed you how your brain works, Mind Performance Hacks shows you how to make it work better.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    How do we resolve psychological conflict that occurs when our behavior violates our attitudes? Why are we so quick to blame others for their behavior while offering excuses for our own? What should we make of the talking heads on cable TV who argue about the cause of TV violence on children's behavior - whose explanation is correct? Why are reality TV shows, some of which portray contestants as pathetic and dysfunctional, so popular?Questions like these usually provoke different answers from different people, each of whom may attribute his or her answers to "common sense." One person argues that "of course children mimic violence they see on TV - my kids do" while another attributes it to "poor parenting - because my kids don't." Which is it, and why?Research psychologists try to answer these questions as best we can. This book is a brief look at the answers to 10 aspects of human behavior - answers derived from controlled behavioral research that is designed to test various theories about behavior. Certainly, there is more to human behavior than the 10 things I chose for this short book. And there are hundreds of primary sources and research reports that describe the research findings in more depth. They're out there if you'd like to read more.But for those who are new to the field of Experimental Psychology, 10 Things may pique your interest in learning more about the subject. And for those "armchair psychologists" out there who'd like a quick read about the most fascinating creatures on the planet - human beings - I think you'll like it, too.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    'Asking the Right Questions' helps students bridge the gap between simply memorising or blindly accepting information, and the greater challenge of critical analysis and synthesis.

    All chapters in this best-seller have been substantially revised to reflect recent discoveries and new understanding of linguistics and languages.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    The book covers statistical generalizations, statistical syllogisms, and inferences to the best explanation.

    The book is conveniently divided into three sections: Section one shows how language is used in multilingual speech communities and explains the varying patterns of language use. Janet Holmes examines how and why languages change within society and highlights the factors that lead to the displacement of one language by another and sometimes the death of a language. Section two explores social reasons for language change, looking at language change in monolingual communities and the features of a variety of dialects. The author shows how and why differing racial and social groups develop and maintain speech variations. The final section assesses how attitudes to language affect speech and shows that linguistic responses depend on a variety of contextual factors - for example, the status of the person being addressed and our re

    Austin was one of the leading philosophers of the twentieth century. The William James Lectures presented Austin's conclusions in the field to which he directed his main efforts on a wide variety of philosophical problems. These talks became the classic How to Do Things with Words.For this second edition, the editors have returned to Austin's original lecture notes, amending the printed text where it seemed necessary. Students will find the new text clearer, and, at the same time, more faithful to the actual lectures. An appendix contains literal transcriptions of a number of marginal notes made by Austin but not included in the text. Comparison of the text with these annotations provides new dimensions to the study of Austin's work.

    And it’s still short, profusely illustrated…and best of all–fun to read.If you’ve read it before, you’ll rediscover what made Don’t Make Me Think so essential to Web designers and developers around the world. If you’ve never read it, you’ll see why so many people have said it should be required reading for anyone working on Web sites.

    Using the recommended APA undergraduate psychology learning outcomes, the authors establish clear learning objectives for students and tie the text assessment to these objectives.