Her first book, Fresh Eggs Daily, was all about healthy, natural care for chickens. Now comes Duck Eggs Daily, an equally valuable guide to raising ducks for eggs and companionship. This is also a book for chicken keepers who want to add ducks to their flock. While ducks can live happily with chickens, ducks are different in many important ways. Steele provides an information-packed, beautifully photographed how-to for raising – and living with – happy, healthy ducks. She examines every aspect of her ducks’ lives, including duck houses and pools, health care, duck behavior and blending ducks into a chicken flock. She provides a breed chart and a selection of favorite recipes using duck eggs.

    The newly revised Fifth Edition has been significantly updated throughout and features substantially revised art and Running Problems in the book and on the reader Companion Website. Recognized as an extraordinary educator and active learning enthusiast, Dr. Silverthorn incorporates time-tested classroom techniques throughout the book and presents thorough, up-to-date coverage of new scientific discoveries, biotechnology techniques, and treatments of disorders. Dr. Silverthorn also co-authored the accompanying Student Workbook and Instructor Manual, ensuring that these ancillaries reinforce the pedagogical approach of the book.The Fifth Edition includes access to Interactive Physiology(R) 10-System Suite (IP-10), PhysioEx(TM) 8.0, A&P Flix animations in 3D, and The Physiology Place Companion Website. Key Topics: Introduction to Physiology, Molecular Interactions, Compartmentation: Cells and Tissues, Energy and Cellular Metabolism, Membrane Dynamics, Communication, Integration, Homeostasis, Introduction to the Endocrine System, Neurons: Cellular and Network Properties, The Central Nervous System, Sensory Physiology, Efferent Division: Autonomic and Somatic Motor Control, Muscles, Integrative Physiology I: Control of Body Movement, Cardiovascular Physiology, Blood Flow and the Control of Blood Pressure, Blood, Mechanics of Breathing, Gas Exchange and Transport, The Kidneys, Integrative Physiology II: Fluid and Electrolyte Balance, Digestion, Energy Balance and Metabolism, Endocrine Control of Growth and Metabolism, The Immune System, Integrative Physiology III: Exercise, Reproduction and DevelopmentMarket: Intended for those interested in learning the basics of human physiology

    In this title, the treatment is made easy-to-follow by giving step-by-step derivations, explanations and by avoiding advanced mathematics unfamiliar to students. It covers: math and physics thorough review sections; and worked examples, followed by a practice exercise.

    Having just served as Governor of the Federal Reserve, only Mishkin has the unique insider's perspective needed to present the current state of money and banking and explain the latest debates and issues for today s students. By applying a unified analytical framework to the models, "The Economics of Money, Banking, and Financial Markets" makes theory intuitive for students, and the rich array of current, real-world events keeps students motivated. Authoritative, comprehensive, and flexible, the text is easy to integrate into a wide variety of syllabi, and its ancillaries provide complete support when teaching the course."

    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.

    Molecular Cell Biology stands out from its peers in this course in that it provides a clear introduction to the techniques and experiments of scientists past and present, not just an "encyclopedia" of information.  This experimental emphasis, together with a solid pedagogical framework in the chapters, provides the clearest, most cutting-edge text available.

    This edition retains the essence of the original, but has been updated with new features and integrated colour illustrations.

    Offering time-tested problems, conceptual and visual pedagogy, and a state-of-the-art media package, this 11th edition looks to the future of university physics, in terms of both content and approach.

    This book demolishes the conventional notion that there is one true history and one best way to teach it.

    From progressive colors to natural tones, Color Index makes choosing hues for any job easier! Designers will start working with color in exciting new ways and create original, eye-catching designs that pop off the page. It's all the inspiration they need to explore and experiment with color as never before! Just like the other clever little design books in this series, Color Index is portable, packed with inspiration, and neatly packaged in a colorful, sturdy vinyl jacket.

    It offers complete coverage of the basics of hematologic morphology, including examination of the peripheral blood smear, basic maturation of the blood cell lines, and discussions of a variety of clinical disorders. Over 400 photomicrographs, schematic diagrams, and electron micrographs visually clarify hematology from normal cell maturation to the development of various pathologies.Normal Newborn Peripheral Blood Morphology chapter covers the unique normal cells found in neonatal blood.A variety of high-quality schematic diagrams, photomicrographs, and electron micrographs visually reinforce your understanding of hematologic cellular morphology.Spiral binding and compact size make this book easy to use in a laboratory setting.Coverage of common cytochemical stains, along with a summary chart for interpretation, aids in classifying malignant and benign leukoproliferative disorders.Morphologic abnormalities are presented in chapters on erythrocytes and leukocytes, along with a schematic description of each cell, to provide correlations to various disease states.Body Fluids chapter covers the other fluids found in the body besides blood, using images from cytocentrifuged specimens.Updated information on the subtypes of chronic lymphocytic leukemia (CLL) helps you recognize variant forms of CLL you may encounter in the lab.

    Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. "Introduction to Machine Learning" is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. It discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the student can easily move from the equations in the book to a computer program. The book can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods.After an introduction that defines machine learning and gives examples of machine learning applications, the book covers supervised learning, Bayesian decision theory, parametric methods, multivariate methods, dimensionality reduction, clustering, nonparametric methods, decision trees, linear discrimination, multilayer perceptrons, local models, hidden Markov models, assessing and comparing classification algorithms, combining multiple learners, and reinforcement learning.

    The book covers four major topics in field experimentation:

    New to this second edition, Student Workbooks for Books I and II include self-correcting exercises, cumulative vocabulary lists, periodic grammatical reviews, and additional readings.

    Extensively illustrated and user-friendly, the text offers examples pf how knowledge of biochemistry is essential for understanding the molecular basis of health and disease. The 26th edition also features expanded content on results of the Human Genome Project. Perfect as both text and USMLE review.