It also contains descriptions and eight pages of in-utero photographs."

    New chapters cover how to build a personal carb count database, carb counting for insulin pump users, a whole week of meal plans, and much more.

    Self muscle testing is a technique similar to that of applied kinesiology, a technique that people use to gain insight into their own body and mind's healing process. The aim of this book is to empower the reader so that they can begin conducting accurate and reliable self muscle testing as soon as possible.Not all humans have the capacity to accurately self muscle test and this book goes into how to set up the ideal conditions so that this valuable tool can be accessed on a regular and consistent basis. The more people that can successfully self muscle test, the better it is for all beings because muscle testing has the potential to rapidly enhance ones ability to “know thy self.”In this book you will learn about:- The pre-requisites for self muscle testing- How to "Switch on" for accurate testing- How to test without bias- How to test health products, supplements and foods- Some more advanced techniques- and more...

    . ." and "The data bear this out. . . ." But the field of statistics is not just about data. Statistics is the entire process involved in gathering evidence to answer questions about the world, in cases where that evidence happens to be numerical data. Statistics For Dummies is for everyone who wants to sort through and evaluate the incredible amount of statistical information that comes to them on a daily basis. (You know the stuff: charts, graphs, tables, as well as headlines that talk about the results of the latest poll, survey, experiment, or other scientific study.) This book arms you with the ability to decipher and make important decisions about statistical results, being ever aware of the ways in which people can mislead you with statistics. Get the inside scoop on number-crunching nuances, plus insight into how you canDetermine the odds Calculate a standard score Find the margin of error Recognize the impact of polls Establish criteria for a good survey Make informed decisions about experiments This down-to-earth reference is chock-full of real examples from real sources that are relevant to your everyday life: from the latest medical breakthroughs, crime studies, and population trends to surveys on Internet dating, cell phone use, and the worst cars of the millennium. Statistics For Dummies departs from traditional statistics texts, references, supplement books, and study guides in the following ways:Practical and intuitive explanations of statistical concepts, ideas, techniques, formulas, and calculations. Clear and concise step-by-step procedures that intuitively explain how to work through statistics problems. Upfront and honest answers to your questions like, "What does this really mean?" and "When and how I will ever use this?" Chances are, Statistics For Dummies will be your No. 1 resource for discovering how numerical data figures into your corner of the universe.

    The Whole Earth Review called Envisioning Information a "passionate, elegant revelation."

    It is written in an easy-to-remember way which links the theory back to your practical driving experience to help you really understand.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    Hundreds of 3D images take you through each of the body's systems, from skeleton and muscles to the skin and nails. Discover how every aspect of the body functions, how the heart beats, how we breathe, and how the body defends itself. Find out what can go wrong, with descriptions of the ways in which common disorders affect the body's systems.

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    Magnesium is an element that is one of the main building blocks of the body. It is involved in hundreds of body and cellular processes. Yet the great majority of Americans are deficient in magnesium. Because magnesium is essential for normal nerve, muscle, and blood vessel functioning, magnesium deficiency leads to a multiplicity of medication conditions, first and foremost migraine headaches and high blood pressure. The Magnesium Solution for Migraine Headaches explains how magnesium deficiency leaves people vulnerable to migraine attacks, how to use magnesium to overcome this vicious condition, how magnesium is safer and as effective as many prescription drugs, the best types of magnesium products to use, and the dosages that are appropriate for men and women of different ages. Dr. Jay S. Cohen is nationally renowned for his work on avoiding medication side effects via the use of better and safer natural therapies.

    There is a major emphasis on study design, with separate chapt

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    Longevity is a priority when enjoying our dogs, and you will see in this educational ebook there are many tips, hints and dog training activities that can help your dog stay young! Susan Garrett's has owned 6 dogs that have lived well into their teenaged years. Recently "Buzz" Susan's oldest Border Collie helped ring in his 18th New Years Eve celebration. Anti-Aging Tips for Dogs is a collection of articles written to help dog owners 1) keep your young dogs healthy as they age and 2)To keep an older dog comfortable well into their teenaged years. It is a resource that should be in the library of ever dog owner world wide! Author Susan Garrett is not only a multi time world champion in the sport of dog agility but also has been recognized by the "Dog Writers of America" for her award winning book "Shaping Success, The Education of an Unlikely Champion"

    This volume covers the symptoms, causes, diagnosis, treatment (including analgesics and NSAIDS), self-help (including diets and complementary therapies), plus the stresses of living with a chronic condition. It is endorsed by the Fibromyalgia Association.

    In this book, Dr. Sherry Seethaler provides a "bag of tricks" for making sense of science in the news. You'll learn how to think more sensibly about everything from mad cow disease to global warming and make better science-related decisions in both your personal life and as a citizen. You'll begin by understanding how science really works and progresses, and why scientists sometimes disagree. Seethaler helps you assess the possible biases of those who make scientific claims in the media, and place scientific issues in appropriate context, so you can intelligently assess tradeoffs. You'll learn how to determine whether a new study is really meaningful; uncover the difference between cause and mere coincidence; figure out which statistics mean something, and which don't. Finally, drawing on her extensive experience as a science journalist, she reveals the tricks self-interested players use to mislead and confuse you, and points you to sources of information you can actually rely upon. Seethaler's many examples range from genetic engineering of crops to drug treatments for depression, but the techniques she teaches you will be invaluable in understanding any scientific controversy, in any area of science or health.