Bayesian Probability For Babies
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Bayesian Probability for Babies
Fans of Chris Ferrie's Rocket Science for Babies, Astrophysics for Babies, and 8 Little Planets will love this introduction to the basic principles of probability for babies and toddlers! Help your future genius become the smartest baby in the room! It only takes a small spark to ignite a child's mind. If you took a bite out of a cookie and that bite has no candy in it, what is the probability that bite came from a candy cookie or a cookie with no candy? You and baby will find out the probability and discover it through different types of distribution. Yet another Baby University board book full of simple explanations of complex ideas written by an expert for your future genius! If you're looking for baby math books, probability for kids, or more Baby University board books to surprise your little one, look no further! Bayesian Probability for Babies offers fun early learning for your little scientist!
Bayesian Networks
Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.
Emery's Elements of Medical Genetics E-Book
Author: Peter D Turnpenny
language: en
Publisher: Elsevier Health Sciences
Release Date: 2020-12-15
Long recognized as a leading textbook in this fast-moving field, Emery's Elements of Medical Genetics and Genomics offers current, complete information with a strong basis in practical clinical genetics and genomics for medical school and beyond. The 16th Edition of this award-winning text has been thoroughly updated throughout and includes case-based and multiple-choice questions, end-of-chapter summaries, an extensive glossary, and convenient online access, making it an ideal choice for all medical undergraduates as well as postgraduates seeking to improve their understanding and knowledge. - Includes new case-based studies with questions and answers throughout, in addition to multiple-choice self-assessment questions for study and review. - Covers key topics such as pharmacogenetics, personalized medicine, prenatal testing, reproductive genetics, and ethical and legal issues in medical genetics. - Divides the text into three easy-to-use sections: The Scientific Basis of Human Genetics, Genetics in Medicine and Genomic Medicine, and Clinical Genetics, Counseling and Ethics. - Features full-color illustrations and other images that help readers visualize the appearance of genetic disorders and assist with the understanding of complex genetic structures. - Contains learning features such as summary boxes, an extensive glossary of terms, online hyperlinks to important genetics websites and clinical databases, and more. - Presents the extensive knowledge and experience of distinguished editors Peter D. Turnpenny and Sian Ellard, as well as new editor Ruth Cleaver.