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Published by Cambridge University Press, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Published by Cambridge University Press 8/13/2020, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Paperback or Softback. Condition: New. Images as Data for Social Science Research: An Introduction to Convolutional Neural Nets for Image Classification. Book.
Language: English
Published by Cambridge University Press, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Published by Princeton University Press, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
paperback. Condition: Near Fine. Condition Notes: Excellent, unmarked copy with little wear and tight binding. We ship in recyclable American-made mailers. 100% money-back guarantee on all orders.
Language: English
Published by Cambridge University Press, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Published by Cambridge University Press, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Published by Cambridge University Press, Cambridge, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Paperback. Condition: new. Paperback. Images play a crucial role in shaping and reflecting political life. Digitization has vastly increased the presence of such images in daily life, creating valuable new research opportunities for social scientists. We show how recent innovations in computer vision methods can substantially lower the costs of using images as data. We introduce readers to the deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. We then provide guidance and specific instructions for scholars interested in using these methods in their own research. Shows how innovation in computer vision methods can markedly lower the costs of using images as data. Introduces readers to deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. Provides guidance and instruction for scholars interested in using these methods in their own research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Cambridge University Press, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Language: English
Published by Cambridge University Press CUP, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Language: English
Published by Cambridge University Press, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Published by Cambridge University Press, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Published by Cambridge University Press 2020-08-13, 2020
ISBN 10: 1108816851 ISBN 13: 9781108816854
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Published by Cambridge University Press, 2020
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Published by Princeton University Press, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Language: English
Published by Princeton University Press, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Language: English
Published by Princeton University Press, 2022
ISBN 10: 0691222274 ISBN 13: 9780691222271
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Published by Princeton University Press, US, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Add to basketPaperback. Condition: New. A tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fieldsQuantitative analysis is an essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it. Quantitative Social Science is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, including business, economics, education, political science, psychology, sociology, public policy, and data science. Proven in classrooms around the world, this one-of-a-kind textbook engages directly with empirical analysis, showing students how to analyze and interpret data using the tidyverse family of R packages. Data sets taken directly from leading quantitative social science research illustrate how to use data analysis to answer important questions about society and human behavior.Emphasizes hands-on learning, not paper-and-pencil statisticsIncludes data sets from actual research for students to test their skills onCovers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical toolsFeatures a wealth of supplementary exercises, including additional data analysis exercises and programming exercisesOffers a solid foundation for further studyComes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides.
Language: English
Published by Princeton University Press, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Published by Princeton University Press, 2022
ISBN 10: 0691222274 ISBN 13: 9780691222271
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Published by Princeton University Press, US, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Paperback. Condition: New. A tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fieldsQuantitative analysis is an essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it. Quantitative Social Science is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, including business, economics, education, political science, psychology, sociology, public policy, and data science. Proven in classrooms around the world, this one-of-a-kind textbook engages directly with empirical analysis, showing students how to analyze and interpret data using the tidyverse family of R packages. Data sets taken directly from leading quantitative social science research illustrate how to use data analysis to answer important questions about society and human behavior.Emphasizes hands-on learning, not paper-and-pencil statisticsIncludes data sets from actual research for students to test their skills onCovers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical toolsFeatures a wealth of supplementary exercises, including additional data analysis exercises and programming exercisesOffers a solid foundation for further studyComes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides.
Language: English
Published by Princeton University Press, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Published by Princeton University Press, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Published by Princeton University Press, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Published by Princeton University Press, 2022
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Published by Princeton University Press, 2022
ISBN 10: 0691222274 ISBN 13: 9780691222271
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Published by Princeton University Press, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Add to basketPaperback. Condition: Brand New. 440 pages. 9.75x6.75x1.00 inches. In Stock.
Language: English
Published by Princeton University Press, 2022
ISBN 10: 0691222282 ISBN 13: 9780691222288
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Language: English
Published by Princeton University Press, 2022
ISBN 10: 0691222274 ISBN 13: 9780691222271
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