Children's Books in Print, 2007 PDF Download

Author:
Publisher:
ISBN: 9780835248518
Category : Authors
Languages : en
Pages :

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Author: K10c Prod Llc
Publisher:
ISBN: 9780842375627
Category :
Languages : en
Pages : 0

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Author: James M.. Fiore
Publisher:
ISBN: 9788172247782
Category : Linear integrated circuits
Languages : en
Pages : 0

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The goal of this book is to encourage the reader to become proficient in the analysis and design of circuits utilizing modern linear integrated circuits. It progresses from the fundamental circuit building blocks through to analog and digital conversion systems. A methodical step-by-step presentation introduces the basic idealized operational amplifiers and eventually examines practical limitations in great detail. Each chapter has a problem set and contains extended topic to present extra discussion and details about the subject.

Author: Peter Bruce
Publisher: "O'Reilly Media, Inc."
ISBN: 1491952911
Category : Computers
Languages : en
Pages : 322

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Book Description
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Author: Stuart A. Kauffman
Publisher: Oxford University Press
ISBN: 0199826676
Category : Science
Languages : en
Pages : 958

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Stuart Kauffman here presents a brilliant new paradigm for evolutionary biology, one that extends the basic concepts of Darwinian evolution to accommodate recent findings and perspectives from the fields of biology, physics, chemistry and mathematics. The book drives to the heart of the exciting debate on the origins of life and maintenance of order in complex biological systems. It focuses on the concept of self-organization: the spontaneous emergence of order that is widely observed throughout nature Kauffman argues that self-organization plays an important role in the Darwinian process of natural selection. Yet until now no systematic effort has been made to incorporate the concept of self-organization into evolutionary theory. The construction requirements which permit complex systems to adapt are poorly understood, as is the extent to which selection itself can yield systems able to adapt more successfully. This book explores these themes. It shows how complex systems, contrary to expectations, can spontaneously exhibit stunning degrees of order, and how this order, in turn, is essential for understanding the emergence and development of life on Earth. Topics include the new biotechnology of applied molecular evolution, with its important implications for developing new drugs and vaccines; the balance between order and chaos observed in many naturally occurring systems; new insights concerning the predictive power of statistical mechanics in biology; and other major issues. Indeed, the approaches investigated here may prove to be the new center around which biological science itself will evolve. The work is written for all those interested in the cutting edge of research in the life sciences.

Author: F. M. Martin
Publisher:
ISBN:
Category : Nuclear energy
Languages : en
Pages : 212

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Author: Kevin P. Murphy
Publisher: MIT Press
ISBN: 0262369303
Category : Computers
Languages : en
Pages : 858

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A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.

Author: Lawson, Tim
Publisher: Univ. Press of Mississippi
ISBN: 9781604736854
Category :
Languages : en
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Author: Michael Angrick
Publisher: Springer Science & Business Media
ISBN: 9400757123
Category : Law
Languages : en
Pages : 282

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Factor X: Re-source—Designing the Recycling Society explores the role of recycling in efforts to achieve the sustainable world envisioned in the Federal Environment Ministry’s Resource Efficiency Programme, known as ProgRess. The chapters build a roadmap to a Recycling Society in which the decoupling of resource consumption and economic growth is accomplished.

Author: Yohan Payan
Publisher: World Bank Publications
ISBN: 0128040602
Category : Medical
Languages : en
Pages : 44

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Biomechanics of Living Organs: Hyperelastic Constitutive Laws for Finite Element Modeling is the first book to cover finite element biomechanical modeling of each organ in the human body. This collection of chapters from the leaders in the field focuses on the constitutive laws for each organ. Each author introduces the state-of-the-art concerning constitutive laws and then illustrates the implementation of such laws with Finite Element Modeling of these organs. The focus of each chapter is on instruction, careful derivation and presentation of formulae, and methods. When modeling tissues, this book will help users determine modeling parameters and the variability for particular populations. Chapters highlight important experimental techniques needed to inform, motivate, and validate the choice of strain energy function or the constitutive model. Remodeling, growth, and damage are all covered, as is the relationship of constitutive relationships of organs to tissue and molecular scale properties (as net organ behavior depends fundamentally on its sub components). This book is intended for professionals, academics, and students in tissue and continuum biomechanics. Covers hyper elastic frameworks for large tissue deformations Considers which strain energy functions are the most appropriate to model the passive and active states of living tissue Evaluates the physical meaning of proposed energy functions