You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

    Abundantly illustrated and containing a wide variety of exercises, Genki is sure to bring vigor to your classroom! Though primarily meant for use in college-level classes, it is also a good guide for independent learners and is a nice resource book for teachers of Japanese. Genki's authors teach at Kansai Gaidai University, which hosts the largest number of North American students spending their junior year in Japan.

    Longer training, ever more advanced technologies—neither seems to prevent grievous errors. But in a hopeful turn, acclaimed surgeon and writer Atul Gawande finds a remedy in the humblest and simplest of techniques: the checklist. First introduced decades ago by the U.S. Air Force, checklists have enabled pilots to fly aircraft of mind-boggling sophistication. Now innovative checklists are being adopted in hospitals around the world, helping doctors and nurses respond to everything from flu epidemics to avalanches. Even in the immensely complex world of surgery, a simple ninety-second variant has cut the rate of fatalities by more than a third.In riveting stories, Gawande takes us from Austria, where an emergency checklist saved a drowning victim who had spent half an hour underwater, to Michigan, where a cleanliness checklist in intensive care units virtually eliminated a type of deadly hospital infection. He explains how checklists actually work to prompt striking and immediate improvements. And he follows the checklist revolution into fields well beyond medicine, from disaster response to investment banking, skyscraper construction, and businesses of all kinds.An intellectual adventure in which lives are lost and saved and one simple idea makes a tremendous difference, The Checklist Manifesto is essential reading for anyone working to get things right.

    What makes an operating system modern? According to author Andrew Tanenbaum, it is the awareness of high-demand computer applications--primarily in the areas of multimedia, parallel and distributed computing, and security. The development of faster and more advanced hardware has driven progress in software, including enhancements to the operating system. It is one thing to run an old operating system on current hardware, and another to effectively leverage current hardware to best serve modern software applications. If you don't believe it, install Windows 3.0 on a modern PC and try surfing the Internet or burning a CD. Readers familiar with Tanenbaum's previous text, Operating Systems, know the author is a great proponent of simple design and hands-on experimentation. His earlier book came bundled with the source code for an operating system called Minux, a simple variant of Unix and the platform used by Linus Torvalds to develop Linux. Although this book does not come with any source code, he illustrates many of his points with code fragments (C, usually with Unix system calls). The first half of Modern Operating Systems focuses on traditional operating systems concepts: processes, deadlocks, memory management, I/O, and file systems. There is nothing groundbreaking in these early chapters, but all topics are well covered, each including sections on current research and a set of student problems. It is enlightening to read Tanenbaum's explanations of the design decisions made by past operating systems gurus, including his view that additional research on the problem of deadlocks is impractical except for "keeping otherwise unemployed graph theorists off the streets." It is the second half of the book that differentiates itself from older operating systems texts. Here, each chapter describes an element of what constitutes a modern operating system--awareness of multimedia applications, multiple processors, computer networks, and a high level of security. The chapter on multimedia functionality focuses on such features as handling massive files and providing video-on-demand. Included in the discussion on multiprocessor platforms are clustered computers and distributed computing. Finally, the importance of security is discussed--a lively enumeration of the scores of ways operating systems can be vulnerable to attack, from password security to computer viruses and Internet worms. Included at the end of the book are case studies of two popular operating systems: Unix/Linux and Windows 2000. There is a bias toward the Unix/Linux approach, not surprising given the author's experience and academic bent, but this bias does not detract from Tanenbaum's analysis. Both operating systems are dissected, describing how each implements processes, file systems, memory management, and other operating system fundamentals. Tanenbaum's mantra is simple, accessible operating system design. Given that modern operating systems have extensive features, he is forced to reconcile physical size with simplicity. Toward this end, he makes frequent references to the Frederick Brooks classic The Mythical Man-Month for wisdom on managing large, complex software development projects. He finds both Windows 2000 and Unix/Linux guilty of being too complicated--with a particular skewering of Windows 2000 and its "mammoth Win32 API." A primary culprit is the attempt to make operating systems more "user-friendly," which Tanenbaum views as an excuse for bloated code. The solution is to have smart people, the smallest possible team, and well-defined interactions between various operating systems components. Future operating system design will benefit if the advice in this book is taken to heart. --Pete Ostenson

    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

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    But what if you could have your computer do them for you?In "Automate the Boring Stuff with Python," you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to: Search for text in a file or across multiple filesCreate, update, move, and rename files and foldersSearch the Web and download online contentUpdate and format data in Excel spreadsheets of any sizeSplit, merge, watermark, and encrypt PDFsSend reminder emails and text notificationsFill out online formsStep-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in "Automate the Boring Stuff with Python.""

    This best-selling, student-friendly book contains clear, step-by-step explanations with comprehensive, stimulating, and challenging material that prepares users for real on-the-job situations. Featuring case studies, state-of-the-art scans, algorithms, protocols, and the inclusion of areas above and beyond the DOT protocols, the tenth edition effectively prepares students for success. The assessment and emergency care sections provide the most up-to-date strategies for providing competent care; and the enrichment sections further enhance students ability to assess and manage ill and injured patients in prehospital environments. The text s table of contents is organized to follow the National EMS Educational Standards."

    The book covers four major topics in field experimentation:

    Intended for introductory courses in financial and managerial accounting in the areas of government or public policy and management, not-for-profit management, and health policy and management, this texts addresses financial and managerial accounting within the three major areas of the public sector - government, health, and not-for-profit.

    Physician, researcher, and award-winning science writer, Siddhartha Mukherjee examines cancer with a cellular biologist’s precision, a historian’s perspective, and a biographer’s passion. The result is an astonishingly lucid and eloquent chronicle of a disease humans have lived with - and perished from - for more than five thousand years. The story of cancer is a story of human ingenuity, resilience, and perseverance, but also of hubris, paternalism, and misperception. Mukherjee recounts centuries of discoveries, setbacks, victories, and deaths, told through the eyes of his predecessors and peers, training their wits against an infinitely resourceful adversary that, just three decades ago, was thought to be easily vanquished in an all-out “war against cancer.” The book reads like a literary thriller with cancer as the protagonist. From the Persian Queen Atossa, whose Greek slave cut off her malignant breast, to the nineteenth-century recipients of primitive radiation and chemotherapy to Mukherjee’s own leukemia patient, Carla, The Emperor of All Maladies is about the people who have soldiered through fiercely demanding regimens in order to survive—and to increase our understanding of this iconic disease. Riveting, urgent, and surprising, The Emperor of All Maladies provides a fascinating glimpse into the future of cancer treatments. It is an illuminating book that provides hope and clarity to those seeking to demystify cancer.

    In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications

    Why are so many RNs dropping out of health care's largest profession? How will the lack of skilled, experienced caregivers affect patients? These are some of the questions addressed by Suzanne Gordon's definitive account of the world's nursing crisis. In Nursing against the Odds, one of North America's leading health care journalists draws on in-depth interviews, research studies, and extensive firsthand reporting to help readers better understand the myriad causes of and possible solutions to the current crisis.Gordon examines how health care cost cutting and hospital restructuring undermine the working conditions necessary for quality care. She shows how the historically troubled workplace relationships between RNs and physicians become even more dysfunctional in modern hospitals. In Gordon's view, the public image of nurses continues to suffer from negative media stereotyping in medical shows on television and from shoddy press coverage of the important role RNs play in the delivery of health care.Gordon also identifies the class and status divisions within the profession that hinder a much-needed defense of bedside nursing. She explains why some policy panaceas--hiring more temporary workers, importing RNs from less-developed countries--fail to address the forces that drive nurses out of their workplaces. To promote better care, Gordon calls for a broad agenda that includes safer staffing, improved scheduling, and other policy changes that would give nurses a greater voice at work. She explores how doctors and nurses can collaborate more effectively and what medical and nursing education must do to foster such cooperation. Finally, Gordon outlines ways in which RNs can successfully take their case to the public while campaigning for health care system reform that actually funds necessary nursing care.

    As it successfully integrates the various functions of management, the book establishes a dialogue with managers from a variety of fields. The authors examine managerial issues concerning defining the manager's terrain, planning, organizing, leading and controlling. For managers of all kinds.

    With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer's memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R's package system and debugging toolsPractice and apply R programming concepts as you learn them