Machine learning with R / / Brett Lantz

• Record Nr.: UNINA9910790503303321
• Autore: Lantz Brett
• Pubbl/distr/stampa: Birmingham : , : Packt Publishing, , 2013
• ISBN: 1-68015-358-7; 1-78216-215-1
• Edizione: [1st edition]
• Descrizione fisica: 1 online resource (396 p.)
• Collana: Community experience distilled
• Soggetti: Machine learning - Statistical methods; R (Computer program language); Programming languages (Electronic computers)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Includes index.
• Sommario/riassunto: R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning. Harness the power of R for statistical computing and data science Use R to apply common machine learning algorithms with real-world applications Prepare, examine, and visualize data for analysis Understand how to choose between machine learning models Packed with clear instructions to explore, forecast, and classify data In Detail Machine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of "big data" and "data science". Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning. Whether you are new to data science or a veteran, machine learning with R offers a powerful set of methods for quickly and easily gaining insight from your data. "Machine Learning with R" is a practical tutorial that uses hands-on examples to step through real-world application of machine learning. Without shying away from the technical details, we will explore Machine Learning with R using clear and practical examples. Well-suited to machine learning beginners or ; those with experience. Explore R to find the answer to all of your questions. How can we use machine learning to transform data into action? Using practical examples, we will explore how to prepare data for analysis, choose a machine learning method, and measure the success of the process. We will learn how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data. "Machine Learning with R" will provide you with the analytical tools you need to quickly gain insight from complex data.

International adoption [[electronic resource] ] : global inequalities and the circulation of children / / edited by Diana Marre and Laura Briggs

• Record Nr.: UNINA9910778026403321
• Autore: Briggs Laura
• Pubbl/distr/stampa: New York, : New York University Press, c2009
• ISBN: 0-8147-6447-9; 0-8147-9590-0; 1-4416-1573-3
• Descrizione fisica: 1 online resource (321 p.)
• Altri autori (Persone): MarreDiana; BriggsLaura <1964->
• Disciplina: 362.734
• Soggetti: Intercountry adoption; Adoption
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Includes index.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Frontmatter -- Contents -- Acknowledgments -- Introduction -- 1 The Movement of Children for International Adoption -- 2 International Adoption: Lessons from Hawai’i -- 3 The Social Temporalities of Adoption and the Limits of Plenary Adoption -- 4 The Desire for Parenthood among Lesbians and Gay Men -- 5 Refiguring Kinship in ; the Space of Adoption -- 6 The Transnational Adoption of a Related Child in Québec, Canada -- 7 Baby-Bearing Storks -- 8 Transnational Connections and Dissenting Views -- 9 International Adoption in Russia -- 10 The Medicalization of Adoption in and from Peru -- 11 Children, Individuality, Family -- 12 “We Do Not Have Immigrant Children at Th is School, We Just Have Children Adopted from Abroad” -- 13 Routes to the Roots -- 14 Return Journeys and the Search for Roots -- 15 Mothers for Others -- 16 Seeking Sisters -- About the Contributors -- Index
• Sommario/riassunto: In the past two decades, transnational adoption has exploded in scope and significance, growing up along increasingly globalized economic relations and the development and improvement of reproductive technologies. A complex and understudied system, transnational adoption opens a window onto the relations between nations, the inequalities of the rich and the poor, and the history of race and racialization, Transnational adoption has been marked by the geographies of unequal power, as children move from poorer countries and families to wealthier ones, yet little work has been done to synthesize its complex and sometimes contradictory effects.Rather than focusing only on the United States, as much previous work on the topic does, International Adoption considers the perspectives of a number of sending countries as well as other receiving countries, particularly in Europe. The book also reminds us that the U.S. also sends children into international adoptions—particularly children of color. The book thus complicates the standard scholarly treatment of the subject, which tends to focus on the tensions between those who argue that transnational adoption is an outgrowth of American wealth, power, and military might (as well as a rejection of adoption from domestic foster care) and those who maintain that it is about a desire to help children in need.