Do you have what it takes to save the day? Can you keep your cool in a crisis, ensure your own survival, and protect your home and family no matter what? Don't worry, we've got you covered. Be a Survivor This newly revised and updated manual is packed with life-saving resources. Easy-to-follow tips, step-by-step illustrations, and simple, effective, real-world strategies cover essential pandemic health and safety guidelines and much, much more-everything from hurricanes to blizzards, car troubles to floods to angry raccoons. Prepare for Anything As the saying goes, fortune favors the prepared-and this book is packed with the tools and skills, the checklists and drills you need to prepare for the worst, and perform at your best no matter what happens. Pitch In In the aftermath of a major disaster, it's a great feeling to be able to help out friends, neighbors, and the larger community. Whether you want to lead a search-and-rescue team or stay home with a victory garden, this book is packed with inspiration for not just surviving but thriving. Outdoor Life brings its millions of readers the best in outdoor recreation and survival topics through their magazine and website, as well as a popular survival blog, and a series of best-selling survival manuals. Book jacket.
Over 150 practical tips and guides that will help safeguard your family during a pandemic. COVID-19 has changed the world and touched the lives of millions. Yet this may be just the first of a potentially terrifying wave of new and lethal pandemics that Governments are ill equipped to handle. New York Times Bestselling author Tim MacWelch and emergency management expert Joseph Pred provide expert and proven advice that can save you and your family when no-one else can. Learn how to create your own facemasks, stock your pantry, and quarantine safely in your own home. With over 150 clearly illustrated survival tips, The Essential Pandemic Survival Guide is the best way that you can protect your family from the lethal impact of a global pandemic. Topics include: • Masks and gloves: What you need to know. How to use properly, common do’s and don’ts • DIY clean suit • Hand sanitizer • Your ultimate first-aid kit • Create an isolation room at home, if you must (and how to make that decision) • How to stock up sensibly for a potential lockdown. • The Ultimate Pandemic Checklist: Food, water, medical supplies, pet care, toiletries, personal items, and more • Help others deal with stress and anxiety • Manage your own mood and mental state • Care for pets in a pandemic • Make a family emergency plan • Help your local community prepare for disasters • 12-month schedule for checking on plans and preparedness with family • Put together your toolkit • Disinfect water • Chart your survival priorities • Pack your bug-out bag
From break-ins to basement flooding to broken bones, this guide has everything you need to be prepared for any emergency that comes your way. Who’s better suited to write a book about handling emergencies than an Emergency and Risk Management Consultant and the CEO of Mutual Aid Response Services (MARS)? Joseph Pred is the go-to-guy for assessing and handling emergencies. When you combine his knowledge with that of the experts at Outdoor Life magazine, what do you get? An epic book filled with lifesaving skills. This book also covers what to do before the first responders arrive...or if they never do. Basic Tools & Skills: Everything you need to know to assess and start handling an emergency. From stocking a first aid kit and treating burns, cuts and broken bones, to protecting yourself when using pepper spray and performing CPR. Home and Family Safety: Protect your house and keep you and your family safe. Learn how to deal with a lost child, handle house fires, public transit scares, car accidents, and help a sick or hurt pet. Community Safety: All the ways to help your neighbors and keep your community safe. From what to do if you see a house being broken into and dealing with school tragedies, to coping with a major natural disaster and handling a toxic spill—and everything in between. When disaster strikes you want to be ready, and you can be with the Emergency Survival Manual.
The New York Times bestselling author of How to Survive Anything shares 130+ safety and survival tips for the next pandemic. COVID-19 has changed the world and touched the lives of millions. Yet this may be just the first of a potentially terrifying wave of new and lethal pandemics that governments are ill equipped to handle. New York Times bestselling author Tim MacWelch and FEMA certified survival expert Joseph Pred provide practical, proven advice that can save the lives of you and your family. Learn how to create your own facemasks, stock your pantry, and quarantine safely in your own home. With more than 130 clearly illustrated survival tips, The Essential Pandemic Survival Guide is your comprehensive go-to guide for staying safe in the face of a global pandemic.
A fully illustrated, step-by-step survival guide that shows everything from extreme wilderness-conquering tactics to lifesaving first aid. Stave off hyena attacks, light a fire with chocolate, and outride an avalanche with How to Survive: The Handbook for the Modern Hero. Outdoors enthusiasts and safety gurus alike need look no further than this practical, hands-on guidebook that will help you conquer any situation with cheeky humor and simplified instructions, including tutorials on how to: - Survive a shipwreck - Spot and treat a concussion - Prepare for social collapse - Catch backyard game - Navigate out of a swamp - Use a fire plank - Drive on black ice - Catch a fish bare-handed - Fill sandbags correctly - Wrap a sling - Spike an assailant - Outride an avalanche - Perform lifesaving first aid Presented in the bold new visual style of the award-winning Show Me How series, drawing on the best of information technology and graphic-novel communication, this is an innovative reference book that can and will be enjoyed as a work of art and as a quirky, thoughtful gift. From basic first aid to battling wild animals, 175 things every modern-day survivor needs to know—one step at a time. Packed with useful hands-on tutorials, How to Survive is a real-life resource that can turn anyone into an expert in any situation.
Presents advice for survival techniques that can be used in different types of emergency situations, discussing such scenarios as floods, fires, hurricanes, boating accidents, burglary, heat attacks, snake bites, and frostbite.
This volume offers a Lexical-Functional Grammar (LFG) analysis of the morphosyntax of Barayin, a Chadic language spoken by about 6000 people in the Guera region of Chad. The core chapters of the book draw on rich empirical data to provide analyses of the basic clause, noun phrases, verb phrases, and serial verb constructions. The version of LFG adopted here includes two recent innovations: the first is minimal c-structure, which results in simpler phrase structure representations; the second is the assumption that glue semantics accounts for argument selection, rejecting the need for a level of a-structure or for Completeness and Coherence in f-structure. Argument sharing in serial verb constructions can thus be modeled in a connected s-structure. This method of modeling semantic composition in complex predicates is extended to directional and associated motion complex predicates in Choctaw and Wambaya, removing the need to appeal to a special mechanism to unite semantic forms in such constructions.
This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, interpretation and evaluation. Complete Stata and R codes are provided throughout the text, with additional code (plus SAS), derivations and data provided on the book's website. Written for the practising researcher, the text begins with an examination of risk and rate ratios, and of the estimating algorithms used to model count data. The book then gives an in-depth analysis of Poisson regression and an evaluation of the meaning and nature of overdispersion, followed by a comprehensive analysis of the negative binomial distribution and of its parameterizations into various models for evaluating count data.
Make the most of R’s extensive toolset R Projects For Dummies offers a unique learn-by-doing approach. You will increase the depth and breadth of your R skillset by completing a wide variety of projects. By using R’s graphics, interactive, and machine learning tools, you’ll learn to apply R’s extensive capabilities in an array of scenarios. The depth of the project experience is unmatched by any other content online or in print. And you just might increase your statistics knowledge along the way, too! R is a free tool, and it’s the basis of a huge amount of work in data science. It's taking the place of costly statistical software that sometimes takes a long time to learn. One reason is that you can use just a few R commands to create sophisticated analyses. Another is that easy-to-learn R graphics enable you make the results of those analyses available to a wide audience. This book will help you sharpen your skills by applying them in the context of projects with R, including dashboards, image processing, data reduction, mapping, and more. Appropriate for R users at all levels Helps R programmers plan and complete their own projects Focuses on R functions and packages Shows how to carry out complex analyses by just entering a few commands If you’re brand new to R or just want to brush up on your skills, R Projects For Dummies will help you complete your projects with ease.
Summary Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learning, preparing you to successfully build and deploy powerful ML systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning systems help you find valuable insights and patterns in data, which you'd never recognize with traditional methods. In the real world, ML techniques give you a way to identify trends, forecast behavior, and make fact-based recommendations. It's a hot and growing field, and up-to-speed ML developers are in demand. About the Book Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems. What's Inside Predicting future behavior Performance evaluation and optimization Analyzing sentiment and making recommendations About the Reader No prior machine learning experience assumed. Readers should know Python. About the Authors Henrik Brink, Joseph Richards and Mark Fetherolf are experienced data scientists engaged in the daily practice of machine learning. Table of Contents PART 1: THE MACHINE-LEARNING WORKFLOW What is machine learning? Real-world data Modeling and prediction Model evaluation and optimization Basic feature engineering PART 2: PRACTICAL APPLICATION Example: NYC taxi data Advanced feature engineering Advanced NLP example: movie review sentiment Scaling machine-learning workflows Example: digital display advertising
Many books teach computational statistics. Until now, however, none has shown how to write a good program. This book gives statisticians, biostatisticians and methodologically-oriented researchers the tools they need to develop high-quality statistical software. Topics include how to: Program in Fortran 95 using a pseudo object-oriented style Write accurate and efficient computational procedures Create console applications Build dynamic-link libraries (DLLs) and Windows-based software components Develop graphical user interfaces (GUIs) Through detailed examples, readers are shown how to call Fortran procedures from packages including Excel, SAS, SPSS, S-PLUS, R, and MATLAB. They are even given a tutorial on creating GUIs for Fortran computational code using Visual Basic.NET. This book is for those who want to learn how to create statistical applications quickly and effectively. Prior experience with a programming language such as Basic, Fortran or C is helpful but not required. More experienced programmers will learn new strategies to harness the power of modern Fortran and the object-oriented paradigm. This may serve as a supplementary text for a graduate course on statistical computing. From the reviews: "This book should be read by all statisticians, engineers, and scientists who want to implement an algorithm as a computer program. The book is the best introduction to programming that I have ever read. I value it as one of my important reference books in my personal library." Melvin J. Hinich for Techonmetrics, November 2006 "Overall, the book is well written and provides a reasonable introduction to the use of modern versions of Fortran for statistical computation. The real thrust of the book is building COM interfaces using Fortran, and it will no doubt be most useful to anyone who needs to build such interfaces." Journal of the American Statistical Association, June 2006 "The book is well written and is divided into chapters and sections which are coherent...Overall the book seems like a good resource for someone that already knows some dialect of FORTRAN and wants to learn a bit about what is new in FORTRAN 95..." Robert Gentleman for the Journal of Statistical Software, December 2006
Gain expert guidance on how to successfully develop machine learning models in Python and build your own unique data platforms Key FeaturesGain a full understanding of the model production and deployment processBuild your first machine learning model in just five minutes and get a hands-on machine learning experienceUnderstand how to deal with common challenges in data science projectsBook Description Where there’s data, there’s insight. With so much data being generated, there is immense scope to extract meaningful information that’ll boost business productivity and profitability. By learning to convert raw data into game-changing insights, you’ll open new career paths and opportunities. The Data Science Workshop begins by introducing different types of projects and showing you how to incorporate machine learning algorithms in them. You’ll learn to select a relevant metric and even assess the performance of your model. To tune the hyperparameters of an algorithm and improve its accuracy, you’ll get hands-on with approaches such as grid search and random search. Next, you’ll learn dimensionality reduction techniques to easily handle many variables at once, before exploring how to use model ensembling techniques and create new features to enhance model performance. In a bid to help you automatically create new features that improve your model, the book demonstrates how to use the automated feature engineering tool. You’ll also understand how to use the orchestration and scheduling workflow to deploy machine learning models in batch. By the end of this book, you’ll have the skills to start working on data science projects confidently. By the end of this book, you’ll have the skills to start working on data science projects confidently. What you will learnExplore the key differences between supervised learning and unsupervised learningManipulate and analyze data using scikit-learn and pandas librariesUnderstand key concepts such as regression, classification, and clusteringDiscover advanced techniques to improve the accuracy of your modelUnderstand how to speed up the process of adding new featuresSimplify your machine learning workflow for productionWho this book is for This is one of the most useful data science books for aspiring data analysts, data scientists, database engineers, and business analysts. It is aimed at those who want to kick-start their careers in data science by quickly learning data science techniques without going through all the mathematics behind machine learning algorithms. Basic knowledge of the Python programming language will help you easily grasp the concepts explained in this book.
Cut through the noise and get real results with a step-by-step approach to data science Key Features Ideal for the data science beginner who is getting started for the first time A data science tutorial with step-by-step exercises and activities that help build key skills Structured to let you progress at your own pace, on your own terms Use your physical print copy to redeem free access to the online interactive edition Book DescriptionYou already know you want to learn data science, and a smarter way to learn data science is to learn by doing. The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. You'll learn from real examples that lead to real results. Throughout The Data Science Workshop, you'll take an engaging step-by-step approach to understanding data science. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Data Science Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your data science book. Fast-paced and direct, The Data Science Workshop is the ideal companion for data science beginners. You'll learn about machine learning algorithms like a data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.What you will learn Find out the key differences between supervised and unsupervised learning Manipulate and analyze data using scikit-learn and pandas libraries Learn about different algorithms such as regression, classification, and clustering Discover advanced techniques to improve model ensembling and accuracy Speed up the process of creating new features with automated feature tool Simplify machine learning using open source Python packages Who this book is forOur goal at Packt is to help you be successful, in whatever it is you choose to do. The Data Science Workshop is an ideal data science tutorial for the data science beginner who is just getting started. Pick up a Workshop today and let Packt help you develop skills that stick with you for life.
This textbook summarizes various studies and significant materials on data analytics in spectroscopy. Its rigorous mathematical basis, in-depth description, and numerous examples of applications in chemistry and physics make this book valuable for theorists, practitioners, and students specializing in data processing in spectroscopy, chemometrics, and analytical chemistry. The bibliography briefly describes hundreds of data analytics applications for solving spectroscopic tasks in industrial and research laboratories. This book differs from existing brief reviews and articles on this topic in that it forms, for the first time, the big picture of all kinds of data analytics methods in spectroscopy. The book also provides quickly reproducible computer calculations to illustrate its significant theoretical statements. As such, it can also serve as a practical guide to lecturers in data analytics in the broad field of spectroscopy, including chemometrics and analytical chemistry.
This textbook gives a complete and modern introduction to mathematical logic. The author uses contemporary notation, conventions, and perspectives throughout, and emphasizes interactions with the rest of mathematics. In addition to covering the basic concepts of mathematical logic and the fundamental material on completeness, compactness, and incompleteness, it devotes significant space to thorough introductions to the pillars of the modern subject: model theory, set theory, and computability. Requiring only a modest background of undergraduate mathematics, the text can be readily adapted for a variety of one- or two-semester courses at the upper-undergraduate or beginning-graduate level. Numerous examples reinforce the key ideas and illustrate their applications, and a wealth of classroom-tested exercises serve to consolidate readers' understanding. Comprehensive and engaging, this book offers a fresh approach to this enduringly fascinating and important subject.
Syntax of Scope takes up the issue of relative operator scope in generative grammar and offers a comparative study of quantifiers and interrogative wh-operators.
A leading resource for nearly two decades and a daily reference for thousands of eyecare professionals, the Fifth Edition of Quick Reference Dictionary of Eyecare Terminology continues this tradition and provides the latest terms, concepts, conditions, and important resources in an instant. Janice K. Ledford and Joseph Hoffman have updated and expanded this essential resource to reflect today’s dialect while retaining the core features associated with this user-friendly reference book: accurately defined terms, cross-referencing, acronyms and abbreviations, and a plethora of additional information in the appendices. Compact, concise, and informative, Quick Reference Dictionary of Eyecare Terminology, Fifth Edition, provides quick access to over 3,700 terms and their definitions, including over 400 new words. This pocket-sized companion also contains 25 appendices. Additionally, pronunciations have been added—an attribute users are sure to appreciate. With a history of excellence, an easy-to-use format, and the latest information, Quick Reference Dictionary of Eyecare Terminology, Fifth Edition is a must have for anyone working in eyecare or an eyecare-related industry. Features: An atlas of ocular anatomy drawings Updated list of pertinent web sites Updated drug tables A reading guide Appendices Include: Medical terminology Subjective grading systems Common abbreviations The metric system English-to-Spanish ocular history flow sheet
A deep dive into the programming language of choice for statistics and data With R All-in-One For Dummies, you get five mini-books in one, offering a complete and thorough resource on the R programming language and a road map for making sense of the sea of data we’re all swimming in. Maybe you’re pursuing a career in data science, maybe you’re looking to infuse a little statistics know-how into your existing career, or maybe you’re just R-curious. This book has your back. Along with providing an overview of coding in R and how to work with the language, this book delves into the types of projects and applications R programmers tend to tackle the most. You’ll find coverage of statistical analysis, machine learning, and data management with R. Grasp the basics of the R programming language and write your first lines of code Understand how R programmers use code to analyze data and perform statistical analysis Use R to create data visualizations and machine learning programs Work through sample projects to hone your R coding skill This is an excellent all-in-one resource for beginning coders who'd like to move into the data space by knowing more about R.
Praise for the first edition: “This book would be especially good for the shelf of anyone who already knows nonparametrics, but wants a reference for how to apply those techniques in R.” -The American Statistician This thoroughly updated and expanded second edition of Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses. Two new chapters covering multivariate analyses and big data have been added. Core classical nonparametrics chapters on one- and two-sample problems have been expanded to include discussions on ties as well as power and sample size determination. Common machine learning topics --- including k-nearest neighbors and trees --- have also been included in this new edition. Key Features: Covers a wide range of models including location, linear regression, ANOVA-type, mixed models for cluster correlated data, nonlinear, and GEE-type. Includes robust methods for linear model analyses, big data, time-to-event analyses, timeseries, and multivariate. Numerous examples illustrate the methods and their computation. R packages are available for computation and datasets. Contains two completely new chapters on big data and multivariate analysis. The book is suitable for advanced undergraduate and graduate students in statistics and data science, and students of other majors with a solid background in statistical methods including regression and ANOVA. It will also be of use to researchers working with nonparametric and rank-based methods in practice.
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