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Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies (Springer Series in Statistics)
Published by Springer (edition 1st ed. 2018), 2018
ISBN 10: 3319653032 ISBN 13: 9783319653037
Language: English
Hardcover. Condition: Very Good. 1st ed. 2018. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Targeted Learning in Data Science. Causal Inference for Complex Longitudinal Studies.
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Add to basketXLII, 640 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Springer Series in Statistics. Sprache: Englisch.
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Targeted Learning in Data Science
Published by Springer International Publishing AG, 2018
ISBN 10: 3319653032 ISBN 13: 9783319653037
Language: English
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Targeted Learning in Data Science
Published by Springer International Publishing AG, 2018
ISBN 10: 3319653032 ISBN 13: 9783319653037
Language: English
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Targeted Learning in Data Science : Causal Inference for Complex Longitudinal Studies
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Targeted Learning in Data Science
Published by Springer International Publishing, 2018
ISBN 10: 3030097366 ISBN 13: 9783030097363
Language: English
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Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies (Springer Series in Statistics)
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Targeted Learning in Data Science : Causal Inference for Complex Longitudinal Studies
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Targeted Learning in Data Science
Published by Springer International Publishing, 2018
ISBN 10: 3030097366 ISBN 13: 9783030097363
Language: English
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Targeted Learning in Data Science
Published by Springer International Publishing, 2018
ISBN 10: 3319653032 ISBN 13: 9783319653037
Language: English
US$ 159.33
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Add to basketCondition: New. Provides essential data analysis tools for answering complex big data questions based on real world dataContains machine learning estimators that provide inference within data science Offers applications that .
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Targeted Learning in Data Science
Published by Springer International Publishing AG, CH, 2018
ISBN 10: 3319653032 ISBN 13: 9783319653037
Language: English
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Add to basketHardback. Condition: New. 2018 ed. This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011.Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics.Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integratinginnovative statistical approaches to advance human health. Dr. Rose's methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics.
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Add to basketHardcover. Condition: Brand New. 1st edition. 640 pages. 9.25x6.25x1.75 inches. In Stock.
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Targeted Learning in Data Science
Published by Springer International Publishing AG, CH, 2018
ISBN 10: 3319653032 ISBN 13: 9783319653037
Language: English
US$ 213.76
Convert currencyUS$ 88.12 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardback. Condition: New. 2018 ed. This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011.Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics.Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integratinginnovative statistical approaches to advance human health. Dr. Rose's methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics.
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Targeted Learning in Data Science
Published by Springer International Publishing, 2018
ISBN 10: 3030097366 ISBN 13: 9783030097363
Language: English
US$ 108.77
Convert currencyUS$ 57.49 shipping from Germany to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides essential data analysis tools for answering complex big data questions based on real world dataContains machine learning estimators that provide inference within data science Offers applications that .
