Jorge and Laura Posada are not the kind of parents who say to their children, "Do as I say." Their parenting mantra instead is, "Let's do it together," and the Posadas have always made good nutrition and fitness a core element of their family lifestyle. Fit Home Team is their formula for getting parents and kids off the couch, arming families with key tools for optimal health, wellness, and overall balance by offering: • A simple guide to eating right • Nutrition-packed kid-friendly recipes • Tips for taking the "work" out of "working out" • Inexpensive seasonal activities for staying fit • An easy-to-follow family progress chart Sixteen percent of children age 2 to 19 are obese. To help face down this tragic national health crisis, the Posadas bring together everything they have learned from sports and athletics, along with caring for their own family, giving parents a complete lesson in fitness, nutrition, and the power of family unity, all at the same time. Fit Home Team is a durable lifestyle change that helps families get fit and stay fit.

"The nation's leading fitness pros reveal their top strategies to get you what you really want ... results"--Cover.

Unleash the power of Python and its robust data science capabilities About This Book Unleash the power of Python 3 objects Learn to use powerful Python libraries for effective data processing and analysis Harness the power of Python to analyze data and create insightful predictive models Unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Who This Book Is For Entry-level analysts who want to enter in the data science world will find this course very useful to get themselves acquainted with Python's data science capabilities for doing real-world data analysis. What You Will Learn Install and setup Python Implement objects in Python by creating classes and defining methods Get acquainted with NumPy to use it with arrays and array-oriented computing in data analysis Create effective visualizations for presenting your data using Matplotlib Process and analyze data using the time series capabilities of pandas Interact with different kind of database systems, such as file, disk format, Mongo, and Redis Apply data mining concepts to real-world problems Compute on big data, including real-time data from the Internet Explore how to use different machine learning models to ask different questions of your data In Detail The Python: Real-World Data Science course will take you on a journey to become an efficient data science practitioner by thoroughly understanding the key concepts of Python. This learning path is divided into four modules and each module are a mini course in their own right, and as you complete each one, you'll have gained key skills and be ready for the material in the next module. The course begins with getting your Python fundamentals nailed down. After getting familiar with Python core concepts, it's time that you dive into the field of data science. In the second module, you'll learn how to perform data analysis using Python in a practical and example-driven way. The third module will teach you how to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis to more complex data types including text, images, and graphs. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. In the final module, we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls. Style and approach This course includes all the resources that will help you jump into the data science field with Python and learn how to make sense of data. The aim is to create a smooth learning path that will teach you how to get started with powerful Python libraries and perform various data science techniques in depth.

A book for all the mentors and assessors of clinical practice in the nursing and midwifery professions who have the crucial task of ensuring that the clinical practice of students attains the standards required for professional registration.

The next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding this insight, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis. This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems. There is a rich and varied set of libraries available in Python for data mining. This book covers a large number, including the IPython Notebook, pandas, scikit-learn and NLTK. Each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will gain a large insight into using Python for data mining, with a good knowledge and understanding of the algorithms and implementations.

A workout book with techniques used by Navy SEALs combined with Cross Fit by a well known Navy SEAL fitness instructor

During the last few decades, commercial gambling has increased substantially throughout the Western world. More people than ever before have access to sources of legalised gambling, leading to bumper revenues for the institutions involved. Naturally enough, this has led to an increased interest in the area of the economics of betting. This book addresses the issues raised by the continued growth of the gambling sector. How can we model the behaviour of people who seemingly act irrationally? What are the implications of different tax policies with regard to gambling? Are casinos capable of taking money away from state-run lotteries and the causes they fund? Can bookmakers’ odds be influenced in such a way as to make the gambling market inefficient? The authors in this volume provide insights based on data from many different countries, including England, the USA, Australia, Spain and Cyprus. This volume brings together work which addresses the economic impact of the huge growth of commercial gambling in the Western world, as well as trying to model the cognitive processes which can explain why individuals are prepared to behave in such apparently irrational ways. This book was published as a special issue of Applied Economics. The academic editor of this journal is Mark P. Taylor.

Grade level: 6, 7, 8, 9, e, i, s, t.

This book illustrates the method of multiple hypotheses with detailed examples and describes the limitations facing all methods (including the method of multiple hypotheses) as the means for constructing knowledge about nature. Author Charles Reichardt explains the method of multiple hypotheses using a range of real-world applications involving the causes of crime, traffic fatalities, and home field advantage in sports. The book describes the benefits of utilizing multiple hypotheses and the inherent limitations within which all methods must operate because all conclusions about nature must remain tentative and forever subject to revision. Nonetheless, the book reveals how the method of multiple hypotheses can produce strong inferences even in the face of the inevitable uncertainties of knowledge. The author also explicates some of the most foundational ideas in philosophy of science including the notions of the underdetermination of theory by data, the Duhem-Quine thesis, and the theory-ladenness of observation. This book will be important reading for advanced undergraduates, graduates, and professional researchers across the social, behavioral, and natural sciences wanting to understand this method and how to apply it to their field of interest.

As part of the pre-registration education for students who intend to enter health care work, periods of work experience are bullt into the curriculum. Students are placed in work settings, generally termed clinical settings, for specified periods, ranging from single days to extended periods of time. Ouring these placements the students are 'supervised' by qualified staff whose first responsibility is to the care of patients. It is therefore important that provi sion is made to support these clinicians in their role of teaching and super vising students. Initiatives have therefore been taken to enhance clinicians' knowledge and skills in the teaching process. The principles and procedures to be used in the supervision and teaching of students are generic in nature and therefore applicable to a number of fields. This book has been prepared for use by a wide range of professionals in health fields. There is particular attention to chiropody/podiatry, dietetics, occupational therapy, orthoptics, physiotherapy, speech and language therapy and radiography, although the principles covered are also applicable to a wider spectrum of professions. The content draws on the experience of clinicians and teachers and will, it is hoped, help to disseminate the good practice which already exists.