A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.
After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.
Автор: Storey William Kelleher Название: Writing History: A Guide for Students ISBN: 0190078413 ISBN-13(EAN): 9780190078416 Издательство: Oxford Academ Цена: 8047.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An indispensable resource for thousands of history students over five editions, Writing History: A Guide for Students provides a wealth of tips and advice to help students research and write essays for history classes. Bringing together practical methods from both history and composition, it covers all aspects of writing about history, including finding and researching topics, interpreting source materials, drawing inferences from sources, and constructing arguments. It concludes with three chapters that discuss writing effective sentences, using precise wording, and revising. Using numerous examples from the works of cultural, political, and social historians, Writing History serves as an ideal text for any history course that asks students to conduct research. The sixth edition offers better guidance on how to begin a research paper and expanded sections on oral history and visual and material sources
Автор: Kelleher Anne Название: Free to Good Home: Collected Short Stories ISBN: 0692408185 ISBN-13(EAN): 9780692408186 Издательство: Неизвестно Цена: 1550.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Kelleher Catherine McArdle, Dombrowski Peter Название: Regional Missile Defense from a Global Perspective ISBN: 0804790647 ISBN-13(EAN): 9780804790642 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 16302.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Regional Missile Defense from a Global Perspective explains the origins, evolution, and implications of the regional approach to missile defense that has emerged since the presidency of George H. W. Bush, and has culminated with the missile defense decisions of President Barack Obama. The Obama administration's overarching concept for American missile defense focuses on developing both a national system of limited ground-based defenses, located in Alaska and California, intended to counter limited intercontinental threats, and regionally-based missile defenses consisting of mobile ground-based technologies like the Patriot PAC-3 system, and sea-based Aegis-equipped destroyer and cruisers.
The volume is intended to stimulate renewed debates in strategic studies and public policy circles over the contribution of regional and national missile defense to global security. Written from a range of perspectives by practitioners and academics, the book provides a rich source for understanding the technologies, history, diplomacy, and strategic implications of the gradual evolution of American missile defense plans. Experts and non-experts alike--whether needing to examine the offense-defense tradeoffs anew, to engage with a policy update, or to better understand the debate as it relates to a country or region--will find this book invaluable. While it opens the door to the debates, however, it does not find or offer easy solutions--because they do not exist.
Автор: Kelleher John D., Tierney Brendan Название: Data Science ISBN: 0262535432 ISBN-13(EAN): 9780262535434 Издательство: MIT Press Рейтинг: Цена: 2700.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges.
The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.
It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.
Описание: Making Love closely reexamines the literary history of sentimentalism in order to open up new ways of understanding the history of sexuality.
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