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1000 tulosta hakusanalla Peter C. Wayner

At the Edge of Empire

At the Edge of Empire

Eric Hinderaker; Peter C. Mancall

Johns Hopkins University Press
2003
pokkari
During the course of the seventeenth century, Europeans and Native Americans came together on the western edge of England's North American empire for a variety of purposes, from trading goods and information to making alliances and war. This blurred and constantly shifting frontier region, known as the backcountry, existed just beyond England's imperial reach on the North American mainland. It became an area of opportunity, intrigue, and conflict for the diverse peoples who lived there. In At the Edge of Empire, Eric Hinderaker and Peter C. Mancall describe the nature of the complex interactions among these interests, examining colorful and sometimes gripping instances of familiarity and uneasiness, acceptance and animosity, and cooperation and conflict, from individual encounters to such vast undertakings as the Seven Years' War. Over time, the European settlers who established farms and trading posts in the backcountry displaced the region's Native inhabitants. Warfare and disease each took a horrifying toll across Indian country, making it easier for immigrants to establish themselves on lands once peopled only by Native Americans. Eventually, these pioneers established economically, culturally, and politically self-sufficient communities that increasingly resented London's claims of sovereignty. As Hinderaker and Mancall show, these resentments helped to shape the ideals that guided the colonists during the American Revolution. The first book in a new Johns Hopkins series, Regional Perspectives on Early America, At the Edge of Empire explores one of British America's most intriguing regions, both widening and deepening our understanding of North America's colonial experience.
Handbook of Environmental Physiology of Fruit Crops

Handbook of Environmental Physiology of Fruit Crops

Bruce Schaffer; Peter C. Andersen

CRC Press Inc
1994
sidottu
These exciting new companion handbooks are the only ones of their kind devoted solely to the effects of environmental variables on the physiology of the world's major fruit and nut crops. Their cosmopolitan scope includes chapters on tropical and temperate zone species written by scientists from several continents. The influence of environmental factors, such as irradiance, temperature, water and salinity on plant physiology and on vegetative and reproductive growth, is comprehensively discussed for each crop. In addition to being a thorough and up-to-date set of textbooks, the organzation of the two volumes makes them an excellent reference tool. Each chapter focuses on a single crop, or a group of genetically or horticulturally related crop, and is appropriately divided into subsections that address individual environmental factors. Some chapters emphasize whole-plant physiology and plant growth and development, while other chapters feature theoretical aspects of plant physiology. Several chapters provide botanical background discussions to enhance understanding of the crop's response to its environment.
Data Mining for Business Analytics

Data Mining for Business Analytics

Galit Shmueli; Peter C. Bruce; Peter Gedeck; Nitin R. Patel

Wiley-Blackwell
2019
sidottu
Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery processA new section on ethical issues in data miningUpdates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their studentsMore than a dozen case studies demonstrating applications for the data mining techniques describedEnd-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presentedA companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
Responsible Data Science

Responsible Data Science

Grant Fleming; Peter C. Bruce

John Wiley Sons Inc
2021
nidottu
Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of “Black box” algorithms that are difficult or impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box modelsDiagnose bias and unfairness within models using multiple metricsAudit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.
Machine Learning for Business Analytics

Machine Learning for Business Analytics

Galit Shmueli; Peter C. Bruce; Amit V. Deokar; Nitin R. Patel

JOHN WILEY SONS INC
2023
sidottu
Machine Learning for Business Analytics Machine learning—also known as data mining or data analytics—is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques and Applications in RapidMiner provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the seventh edition of Machine Learning for Business Analytics, and the first using RapidMiner software. This edition also includes: A new co-author, Amit Deokar, who brings experience teaching business analytics courses using RapidMiner Integrated use of RapidMiner, an open-source machine learning platform that has become commercially popular in recent years An expanded chapter focused on discussion of deep learning techniques A new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.
Machine Learning for Business Analytics

Machine Learning for Business Analytics

Galit Shmueli; Peter C. Bruce; Kuber R. Deokar; Nitin R. Patel

JOHN WILEY SONS INC
2023
sidottu
MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning—also known as data mining or predictive analytics—is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver® Data Mining provides a comprehensive introduction and an overview of this methodology. The fourth edition of this best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, time series forecasting and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This fourth edition of Machine Learning for Business Analytics also includes: An expanded chapter on deep learning A new chapter on experimental feedback techniques, including A/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.
Machine Learning for Business Analytics

Machine Learning for Business Analytics

Galit Shmueli; Peter C. Bruce; Peter Gedeck; Inbal Yahav; Nitin R. Patel

JOHN WILEY SONS INC
2023
sidottu
MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using RAn expanded chapter focused on discussion of deep learning techniquesA new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniquesEnd-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presentedA companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.
Machine Learning for Business Analytics

Machine Learning for Business Analytics

Galit Shmueli; Peter C. Bruce; Mia L. Stephens; Muralidhara Anandamurthy; Nitin R. Patel

JOHN WILEY SONS INC
2023
sidottu
MACHINE LEARNING FOR BUSINESS ANALYTICS An up-to-date introduction to a market-leading platform for data analysis and machine learning Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. offers an accessible and engaging introduction to machine learning. It provides concrete examples and case studies to educate new users and deepen existing users’ understanding of their data and their business. Fully updated to incorporate new topics and instructional material, this remains the only comprehensive introduction to this crucial set of analytical tools specifically tailored to the needs of businesses. Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. readers will also find: Updated material which improves the book’s usefulness as a reference for professionals beyond the classroomFour new chapters, covering topics including Text Mining and Responsible Data ScienceAn updated companion website with data sets and other instructor resources: www.jmp.com/dataminingbookA guide to JMP Pro's new features and enhanced functionality Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. is ideal for students and instructors of business analytics and data mining classes, as well as data science practitioners and professionals in data-driven industries.
Strategy and Politics

Strategy and Politics

Emerson Niou; Peter C. Ordeshook

Routledge
2015
sidottu
Strategy and Politics: An Introduction to Game Theory is designed to introduce students with no background in formal theory to the application of game theory to modeling political processes. This accessible text covers the essential aspects of game theory while keeping the reader constantly in touch with why political science as a whole would benefit from considering this method. Examining the very phenomena that power political machineries—elections, legislative and committee processes, and international conflict, the book attempts to answer fundamental questions about their nature and function in a clear, accessible manner. Included at the end of each chapter is a set of exercises designed to allow students to practice the construction and analysis of political models. Although the text assumes only an elementary-level training in algebra, students who complete a course around this text will be equipped to read nearly all of the professional literature that makes use of game theoretic analysis.
Tendon Surgery of the Hand

Tendon Surgery of the Hand

Jin Bo Tang; Peter C. Amadio; Jean Claude Guimberteau; James Chang

W B Saunders Co Ltd
2012
sidottu
Get the best results from the latest procedures with Tendon Surgery of the Hand, the only reference that offers comprehensive coverage of this complex and challenging area. World-renowned experts guide you through all of the newest techniques and technologies, equipping you to restore optimal function in your patients. It's your one-stop source for mastering today's best approaches to treating tendon injuries and disorders of the hand. Successfully implement hot new repair techniques involving new suture materials, tendon sheath and pulley treatments, vascularized tendon grafts, and recent postoperative rehabilitation methods. Improve your primary flexor tendon repair and rehabilitation treatment planning based on surgical and post-surgical care principles that clearly describe successful global methods and protocols. Benefit from the collective knowledge and experience of an international group of surgeons, investigators, and therapists who offer unique and insightful techniques and advice. See how to perform key techniques with exclusive operative videos online. Access the complete contents online at expertconsult.com.
Organic Chemistry

Organic Chemistry

Vollhardt K. Peter C.; Neil E. Shore

W.H.Freeman Co Ltd
2014
sidottu
With authors who are both accomplished researchers and educators, Vollhardt and Schore’s Organic Chemistry takes a functional group approach with a heavy emphasis on understanding how the structure of a molecule determines how that molecule will function in chemical reactions. By understanding the connection between structure and function, students will better understand mechanisms and solve practical problems in organic chemistry.
The Pivot of Civilization

The Pivot of Civilization

Margaret Sanger; Peter C. Engelman

BLOOMSBURY PUBLISHING PLC
2022
nidottu
Arguably her most important and influential book, this controversial work, first published in 1922 by pioneering birth-control advocate Margaret Sanger, attempted to broaden the still-radical idea of birth control beyond its socialist and feminist roots. Moving away from a single-minded focus on women's reproductive rights to the larger issue of the general health and economic prosperity of the whole human race, Sanger argued that birth control was pivotal to a rational approach toward dealing with the threat of overpopulation and its ruinous consequences in poverty and disease. Through this book Sanger hoped to persuade the medical establishment to assume control over contraceptive distribution, and thereby to lessen the religious, legal, and moral opposition that continued to restrict access to contraceptive information. However important this book is to the history of women's rights, it remains a very problematic work from our more scientifically informed perspective today. In arguing for population control Sanger made frequent reference to the then fashionable "science" of eugenics. She also adopted its rhetoric, using such callous phrases as "the feeble-minded" and the "unfit" and advocating birth control as a means of limiting the breeding of "defectives, delinquents and dependents." Although she incorporated views and terminology commonly held in respectable medical and scientific circles of the day, Sanger's writings on eugenics, and this book in particular, have become fodder for her critics both on the left and the right, who seek to diminish her achievements and obscure what is ultimately a powerful feminist message: when women gain greater control over their fertility, they will improve the human race. This unusual and historically significant book is complemented by a thoughtful and informative introduction by Peter C. Engelman, assistant editor of The Margaret Sanger Papers Project, who provides much insight by placing this work in the context of the age and Sanger's life.
Models, Methods and Applications of Econometrics

Models, Methods and Applications of Econometrics

Greer Phillips; Peter C. B. Phillips

Blackwell Publishers
1993
sidottu
The twenty especially commissioned esays in this volume cover a wide field of recent and topical research dealing with both theory and application of econometrics. The contributors comprise an international and distinguished group of economists, econometricians, modelers and statisticians. The volume will be of wide interest to all those concernedd with modelling, forecasting and other applications of econometrics. The volume is divided into five parts according to separate themes of research that include continuoustime modelling, finite sample theory, dynamic econometric modeling, and empirical applications in macroeconomics, industry and finance. The essays make methodological, empirical and theoretical advances in each of these fields, including many recent topics of intense research such as nonlinear modeling, parameter parsimony, business cycles, Euler equation methodology, rational expectations, vector autoregressions, cointegrated systems, unit roots and semiparametric models. The volume is dedicated to A. R. Bergstrom and contains a review of his research in these various fields and his essay, What is Econometrics?
Dodgers to Damascus

Dodgers to Damascus

Catherine Nixon Cooke; Peter C. Goldmark

TRINITY UNIVERSITY PRESS,U.S.
2025
sidottu
David Lesch is a modern-day Renaissance man whose work has spanned continents and allowed him to explore cultures near and far. An acclaimed scholar, educator, author, and conflict resolution specialist, he has advised five U.S. presidential administrations at the highest levels about the head-spinning political, religious, and cultural complexities of the Middle East. He is the author or editor of seventeen books, including The History of the Middle East since the Rise of Islam, Syria: A Modern History, and The Arab-Israeli Conflict: A History.Long before, as the number one draft pick for the Los Angeles Dodgers in 1980, Lesch followed his American dream, playing with many baseball greats until a shoulder injury sidelined him. He later became a distinguished professor of Middle East studies at Trinity University in San Antonio and was soon tapped by the United Nations, the U.S. State Department, and policy centers and governments internationally.Dodgers to Damascus documents a part of the world that has been shrouded in mystery and plagued by conflict, power struggles, and warfare, and offers a firsthand glimpse inside modern Syria, its neighboring countries, and their connections to the rest of the world. Lesch’s work in Syria resulted in a tenuous relationship with President Bashar al-Assad and many tense situations, including a poisoned meal that almost cost him his life. His encounters with elected officials, diplomats, spies, and conflict resolution specialists have all the elements of a Hollywood thriller and parallel his personal story of loss, crisis, and redemption.Lesch’s work in Syria resulted in a tenuous relationship with President Bashar al-Assad and many tense situations, including a poisoned meal that almost cost him his life. His encounters with elected officials, diplomats, spies, and conflict resolution specialists have all the elements of a Hollywood thriller and parallel his personal story of loss, crisis, and redemption.
Multichannel Retailing

Multichannel Retailing

Huan Liu; Peter C. Verhoef; Lara Lobschat

now publishers Inc
2018
nidottu
Presents an overview of and draws conclusions from extant studies related to multichannel retailing. Academic interest in this topic has increased dramatically, with a large number of new articles being published on this topic as retailers have adopted additional new channels and new channel technologies with unique characteristics, which has further increased the complexity of multichannel retailing. Thus, an updated understanding of how retailers and consumers influence and interact with each other in multichannel retail contexts is required.The authors focus on the following questions: (1) What factors influence channel choices of retailers and customers? (2) How do retailers employ multichannel marketing strategies, and how do customers use different channels to search and purchase during their purchase journey? And (3) How do multichannel strategies and channel selection behavior affect customer outcomes and retailer performance? After presenting the definitions of key terms used in multichannel retailing, the authors introduce their framework. Next, they synthesize existing research and specify the three research questions with six subtopics by considering the perspectives of both customers and retailers. At the end of each subtopic, the authors discuss future research directions derived from research gaps, unresolved issues in practice, and environment changes. The monograph concludes with thoughts about the future of retailing.