How to Land a Top-Paying Federal Job is the ultimate guide to securing a government job, internship, or fellowship. Written by a successful career coach who has climbed the federal career ladder herself and served as a hiring manager, the book steers applicants through every stage of their job searchesùfrom finding unadvertised openings and getting interviews to sealing enviable deals and even get ting promoted. Drawing on interviews with more than 100 federal hiring managers, the book reveals the secrets to impressing these gatekeepers online, on paper, and in personùinformation that is available nowhere else. The updated second edition includes more get-ahead tips; new templates for writing winning applications; expanded directories for internships, fast-track management training programs and fellowships; and the latest helpful websites. Complete with a companion CD filled with sample rTsumTs, checklists, and templates, this indispensable book gives readers the inside scoop on landing some of the nationÆs most secure, well-paying, and rewarding jobsùin all 50 states and abroad!
Malcolm Gladwell, host of the podcast Revisionist History and author of the #1 New York Times bestseller Outliers, offers a powerful examination of our interactions with strangers and why they often go wrong—now with a new afterword by the author. A Best Book of the Year: The Financial Times, Bloomberg, Chicago Tribune, and Detroit Free Press How did Fidel Castro fool the CIA for a generation? Why did Neville Chamberlain think he could trust Adolf Hitler? Why are campus sexual assaults on the rise? Do television sitcoms teach us something about the way we relate to one another that isn’t true? Talking to Strangers is a classically Gladwellian intellectual adventure, a challenging and controversial excursion through history, psychology, and scandals taken straight from the news. He revisits the deceptions of Bernie Madoff, the trial of Amanda Knox, the suicide of Sylvia Plath, the Jerry Sandusky pedophilia scandal at Penn State University, and the death of Sandra Bland—throwing our understanding of these and other stories into doubt. Something is very wrong, Gladwell argues, with the tools and strategies we use to make sense of people we don’t know. And because we don’t know how to talk to strangers, we are inviting conflict and misunderstanding in ways that have a profound effect on our lives and our world. In his first book since his #1 bestseller David and Goliath, Malcolm Gladwell has written a gripping guidebook for troubled times.
Includes the Aerial Warfare In Europe During World War II illustrations pack with over 200 maps, plans, and photos. This book is a comprehensive analysis of an air force, the Luftwaffe, in World War II. It follows the Germans from their prewar preparations to their final defeat. There are many disturbing parallels with our current situation. I urge every student of military science to read it carefully. The lessons of the nature of warfare and the application of airpower can provide the guidance to develop our fighting forces and employment concepts to meet the significant challenges we are certain to face in the future.
Quite simply, test-driven development is meant to eliminate fear in application development. While some fear is healthy (often viewed as a conscience that tells programmers to "be careful!"), the author believes that byproducts of fear include tentative, grumpy, and uncommunicative programmers who are unable to absorb constructive criticism. When programming teams buy into TDD, they immediately see positive results. They eliminate the fear involved in their jobs, and are better equipped to tackle the difficult challenges that face them. TDD eliminates tentative traits, it teaches programmers to communicate, and it encourages team members to seek out criticism However, even the author admits that grumpiness must be worked out individually! In short, the premise behind TDD is that code should be continually tested and refactored. Kent Beck teaches programmers by example, so they can painlessly and dramatically increase the quality of their work.
The only way to learn is to practice! In Machine Learning Bookcamp, you''ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you''ve learned in previous chapters. By the end of the bookcamp, you''ll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technology Machine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that''s exactly what you''ll be doing in Machine Learning Bookcamp. about the book In Machine Learning Bookcamp you''ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you''ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You''ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you''re done working through these fun and informative projects, you''ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what''s inside Code fundamental ML algorithms from scratch Collect and clean data for training models Use popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images and text Deploy ML models to a production-ready environment about the reader For readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.
This book provides a collection of comprehensive research articles on data analytics and applications of wearable devices in healthcare. This Special Issue presents 28 research studies from 137 authors representing 37 institutions from 19 countries. To facilitate the understanding of the research articles, we have organized the book to show various aspects covered in this field, such as eHealth, technology-integrated research, prediction models, rehabilitation studies, prototype systems, community health studies, ergonomics design systems, technology acceptance model evaluation studies, telemonitoring systems, warning systems, application of sensors in sports studies, clinical systems, feasibility studies, geographical location based systems, tracking systems, observational studies, risk assessment studies, human activity recognition systems, impact measurement systems, and a systematic review. We would like to take this opportunity to invite high quality research articles for our next Special Issue entitled “Digital Health and Smart Sensors for Better Management of Cancer and Chronic Diseases” as a part of Sensors journal.
The U.S. Social Security Administration (SSA) provides disability benefits through the Social Security Disability Insurance (SSDI) and Supplemental Security Income (SSI) programs. To receive SSDI or SSI disability benefits, an individual must meet the statutory definition of disability, which is "the inability to engage in any substantial gainful activity [SGA] by reason of any medically determinable physical or mental impairment which can be expected to result in death or which has lasted or can be expected to last for a continuous period of not less than 12 months." SSA uses a five-step sequential process to determine whether an adult applicant meets this definition. Functional Assessment for Adults with Disabilities examines ways to collect information about an individual's physical and mental (cognitive and noncognitive) functional abilities relevant to work requirements. This report discusses the types of information that support findings of limitations in functional abilities relevant to work requirements, and provides findings and conclusions regarding the collection of information and assessment of functional abilities relevant to work requirements.
I wanted to compute 80th term of the Fibonacci series. I wrote the rampant recursive function, int fib(int n){ return (1==n || 2==n) ? 1 : fib(n-1) + fib(n-2); } and waited for the result. I wait… and wait… and wait… With an 8GB RAM and an Intel i5 CPU, why is it taking so long? I terminated the process and tried computing the 40th term. It took about a second. I put a check and was shocked to find that the above recursive function was called 204,668,309 times while computing the 40th term. More than 200 million times? Is it reporting function calls or scam of some government? The Dynamic Programming solution computes 100th Fibonacci term in less than fraction of a second, with a single function call, taking linear time and constant extra memory. A recursive solution, usually, neither pass all test cases in a coding competition, nor does it impress the interviewer in an interview of company like Google, Microsoft, etc. The most difficult questions asked in competitions and interviews, are from dynamic programming. This book takes Dynamic Programming head-on. It first explain the concepts with simple examples and then deep dives into complex DP problems.
