With this practical book, you'll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media.Learn how to apply the tidy text format to NLPUse sentiment analysis to mine the emotional content of textIdentify a document's most important terms with frequency measurementsExplore relationships and connections between words with the ggraph and widyr packagesConvert back and forth between R's tidy and non-tidy text formatsUse topic modeling to classify document collections into natural groupsExamine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages

    Whatever your circumstances, you can create the life you desire by following simple, counterintuitive steps; not the steps society wants you to follow. Unfortunately, you cannot even trust yourself when it comes to creating the life that you desire, because you’re programmed by your past, an accumulation of hundreds of thousands of years, a mind still adapted for a hunter-gatherer time period. What does this mean? It means every day you’re battling your emotions, logic versus emotion. Logically, you want to do one thing, but emotionally, you are drawn to something else. First, if this sounds familiar, then great, because it means you are human. But, if you’re going to win the game of life, you cannot sit around and wait for things to happen, because you’ll be living a life of supreme comfort and sameness; ultimately, a great sin. You are destined for great things, capable of forging dreams and living your aspirations. Maybe you’ve forgotten about this truth: that you are capable, worthy, and ready. Maybe you’ve been beaten into the ground by life, a teacher who doesn’t care if you’re rich or poor, weak or strong, ready or not, because life will continue forward regardless, waiting for no one. Fortunately, there’re things you can do to set yourself apart from the millions that will ultimately suffer and fail. One such thing, perhaps the most powerful of all, is by studying the great, people who have succeeded and who have gone beyond what is humanly thought possible. When it comes to studying someone great, there’s one name that stands tall, Stephen Hawking, a person who has persevered and flourished. Not only has he conquered great adversity, but he has inspired millions around the world with his brilliant mind. There is a reason why people compare him with the once living Albert Einstein, the genius. What follows are Stephen Hawking’s greatest life lessons, gems of wisdom that you can easily apply to your own life, which will help you live a more abundant, stronger life. If you’re in need of inspiration, a boost of confidence, or just a friendly reminder of the wonders in life, you’ve come to the right place. See for yourself why millions study his work and regard him as a genius. Scroll up and grab your copy today.*** Limited time offer ***

    Written in a concise, bulleted outline format, this well-illustrated text offers 500 USMLE-style review questions, answers, and explanations and features comprehensive content and upgraded USMLE Step 1 information.

    Fundamentals of Biostatistics with CD-Rom.

    It follows a more quantitative and design-oriented approach than other texts in the market, helping readers gain a better understanding of important concepts. They'll also discover how material properties relate to the process variables in a given process as well as how to perform manufacturing science and quantitative engineering analysis of manufacturing processes.

    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

    The Fifth Edition features updated information throughout, including new theories and models such as the Healthy Action Process Approach (HAPA) and the Community Readiness Model (CRM), sections on grant writing and preparing a budget, real-life examples of marketing principles and processes, and a new classification system for evaluation approaches and designs. Health Education, Health Promotion, Health Educators, and Program Planning, Models for Program Planning in Health Promotion, Starting the Planning Process, Assessing Needs, Measurement, Measures, Measurement Instruments and Sampling, Mission Statement, Goals, and Objectives, Theories and Models Commonly Used for Health Promotion Interventions, Interventions, Community Organizing and Community Building, Identification and Allocation of Resources, Marketing: Making Sure Programs Respond to Wants and Needs of Consumers, Implementation: Strategies and Associated Concerns, Evaluation: An Overview, Evaluation Approaches and Designs, Data Analysis and Reporting. Intended for those interested in learning the basics of planning, implementing, and evaluating health promotion programs

    It has become popular in recent years because of its simplicity, conciseness, and clarity. This book teaches functional programming as a way of thinking and problem solving, using Haskell, the most popular purely functional language. Rather than using the conventional (boring) mathematical examples commonly found in other programming language textbooks, the author uses examples drawn from multimedia applications, including graphics, animation, and computer music, thus rewarding the reader with working programs for inherently more interesting applications. Aimed at both beginning and advanced programmers, this tutorial begins with a gentle introduction to functional programming and moves rapidly on to more advanced topics. Details about progamming in Haskell are presented in boxes throughout the text so they can be easily found and referred to.

    Written By Two Of Today'S Most Respected Computer Science Educators, Nell Dale And John Lewis, The Text Provides A Broad Overview Of The Many Aspects Of The Discipline From A Generic View Point. Separate Program Language Chapters Are Available As Bundle Items For Those Instructors Who Would Like To Explore A Particular Programming Language With Their Students. The Many Layers Of Computing Are Thoroughly Explained Beginning With The Information Layer, Working Through The Hardware, Programming, Operating Systems, Application, And Communication Layers, And Ending With A Discussion On The Limitations Of Computing. Perfect For Introductory Computing And Computer Science Courses, Computer Science Illuminated, Third Edition's Thorough Presentation Of Computing Systems Provides Computer Science Majors With A Solid Foundation For Further Study, And Offers Non-Majors A Comprehensive And Complete Introduction To Computing.

    It outlines a set of mindsets and habits you can use to help you identify the most impactful parts of your teaching, and put them centre stage.It's about doing less to achieve more.But it's also about being happier and more confident in the classroom. Building stronger routines around the essentials will give you more time and space to appreciate and think creatively about your work.POWER UP YOUR PLANNINGLean Lesson Planning draws on the latest evidence from educational research and cognitive science, to present a concise and coherent framework to help you improve learning experiences and outcomes for your students. It's the evidence-based teacher's guide to planning for learning, and sits alongside books such as Teach Like a Champion, Embedded Formative Assessment, and Visible Learning for Teachers.NOTE If you're looking for ways to short-cut the amount of time you spend planning lessons, then this book is not for you. The approach outlined in Lean Lesson Planning requires effort and practice, that given time, will lead to better teaching and higher quality learning for less input.---CONTENTSACT I Lean foundations1. Defining lean 2. Lean mindsets 3. Lean habits ACT II Habits for planning4. Backwards design 5. Knowing knowledge 6. Checking understanding 7. Efficient strategies 8. Lasting learning 9. Inter-lesson planning ACT III Habits for growing10. Building excellence 11. Growth teaching 12. Collective improvement Lean Lesson Planning is the first instalment in the High Impact Teaching series.

    This thorough revision provides a survey by groups, emphasizing adaptive morphology and physiology, while covering anatomical ground plans and basic developmental patterns. New co-author Richard Fox brings to the revision his expertise as an ecologist, offering a good balance to Ruppert's background as a functional morphologist. Rich illustrations and extensive citations make the book extremely valuable as a teaching tool and reference source.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    

    To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok.In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information (Alan Turing's role in breaking Germany's Enigma code during World War II), and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security.Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.

    This is the book for you because it will help you hit the ground running once you get your license. It is written by an actual, active Realtor. Mario Jannatpour is with RE/MAX Alliance in Louisville, Colorado and what he writes about is based on his experience of what it takes to be successful today as a Realtor. Mario has been a Realtor since 2002. Reader Review: Are you green in real estate or a veteran? Do you know what buyers and sellers are looking for when they are looking at you? What qualities differenciate you from your competition? Mario has helped pin point what today's buyers and sellers are looking for in their real estate agent giving relavent information as well as insight on how you should handle different situations. We all know that honesty is the best policy yet the profession of representation is riddled with pot holes where one can stray. This book will help any new agent or seasoned agent gain a true north when dealing with clients. Mario's first book, Must See Inside, was a great introduction to the real estate business and with this book, The Honest Real Estate Agent, Mario dives deeper on how to "be" a real estate agent which means doing the right thing, always! I sincerely recommend this book for anyone who is getting into the business and wants to get a firm handle of how to "be" great at your job. Addy Saeed, RE/MAX Active Realty (Toronto, Canada)