Published by Cambridge University Press, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
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Published by Cambridge University Press 17 M, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
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Add to basketPaperback. Condition: Very Good. Text Analysis in Python for Social Scientists: Prediction and Classification (Elements in Quantitative and Computational Methods for the Social Sciences) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
Published by Cambridge University Press 02/r /17 M, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
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Published by Cambridge University Press, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
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Published by Cambridge University Press, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Published by Cambridge University Press 3/17/2022, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
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Published by Cambridge University Press 1/21/2021, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Published by Cambridge University Press, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
Language: English
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Published by Cambridge University Press, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Published by Cambridge University Press 21 J, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Add to basketPaperback. Condition: Very Good. Text Analysis in Python for Social Scientists: Discovery and Exploration (Elements in Quantitative and Computational Methods for the Social Sciences) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
Published by Cambridge University Press, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
Language: English
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Published by Cambridge University Press, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Paperback. Condition: new. Paperback. Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it. Text is a fantastic resource for social scientists, but because it is so abundant, and so variable, it can be difficult to extract the information we want. Many basic text analysis methods are available as Python implementations: this Element will teach you when to use which method, how it works, and the Python code to implement it. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Cambridge University Press, Cambridge, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
Language: English
Seller: Grand Eagle Retail, Fairfield, OH, U.S.A.
Paperback. Condition: new. Paperback. Text contains a wealth of information about about a wide variety of sociocultural constructs. Automated prediction methods can infer these quantities (sentiment analysis is probably the most well-known application). However, there is virtually no limit to the kinds of things we can predict from text: power, trust, misogyny, are all signaled in language. These algorithms easily scale to corpus sizes infeasible for manual analysis. Prediction algorithms have become steadily more powerful, especially with the advent of neural network methods. However, applying these techniques usually requires profound programming knowledge and machine learning expertise. As a result, many social scientists do not apply them. This Element provides the working social scientist with an overview of the most common methods for text classification, an intuition of their applicability, and Python code to execute them. It covers both the ethical foundations of such work as well as the emerging potential of neural network methods. This Element provides the working social scientist with an overview of the most common methods for text classification, an intuition of their applicability, and Python code to execute them. It covers both the ethical foundations of such work as well as the emerging potential of neural network methods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Cambridge University Press 02/n /21 J, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Published by Cambridge University Press 2020-12-31, 2020
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Published by Cambridge University Press, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
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Published by Cambridge University Press, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
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Published by Cambridge University Press 2022-03, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
Language: English
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Published by Cambridge University Press, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
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Published by Cambridge University Press, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
Language: English
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Published by Cambridge University Press, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Published by Cambridge University Press, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
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Published by Cambridge University Press, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Published by Cambridge University Press Jan 2021, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware - A practical guide to text analysis with Python: the intuition, the math, the code.
Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
Seller: AussieBookSeller, Truganina, VIC, Australia
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Add to basketPaperback. Condition: new. Paperback. Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it. Text is a fantastic resource for social scientists, but because it is so abundant, and so variable, it can be difficult to extract the information we want. Many basic text analysis methods are available as Python implementations: this Element will teach you when to use which method, how it works, and the Python code to implement it. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Cambridge University Press, Cambridge, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
Language: English
Seller: AussieBookSeller, Truganina, VIC, Australia
US$ 44.84
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Add to basketPaperback. Condition: new. Paperback. Text contains a wealth of information about about a wide variety of sociocultural constructs. Automated prediction methods can infer these quantities (sentiment analysis is probably the most well-known application). However, there is virtually no limit to the kinds of things we can predict from text: power, trust, misogyny, are all signaled in language. These algorithms easily scale to corpus sizes infeasible for manual analysis. Prediction algorithms have become steadily more powerful, especially with the advent of neural network methods. However, applying these techniques usually requires profound programming knowledge and machine learning expertise. As a result, many social scientists do not apply them. This Element provides the working social scientist with an overview of the most common methods for text classification, an intuition of their applicability, and Python code to execute them. It covers both the ethical foundations of such work as well as the emerging potential of neural network methods. This Element provides the working social scientist with an overview of the most common methods for text classification, an intuition of their applicability, and Python code to execute them. It covers both the ethical foundations of such work as well as the emerging potential of neural network methods. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Cambridge University Press, Cambridge, 2022
ISBN 10: 1108958508 ISBN 13: 9781108958509
Language: English
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Add to basketPaperback. Condition: new. Paperback. Text contains a wealth of information about about a wide variety of sociocultural constructs. Automated prediction methods can infer these quantities (sentiment analysis is probably the most well-known application). However, there is virtually no limit to the kinds of things we can predict from text: power, trust, misogyny, are all signaled in language. These algorithms easily scale to corpus sizes infeasible for manual analysis. Prediction algorithms have become steadily more powerful, especially with the advent of neural network methods. However, applying these techniques usually requires profound programming knowledge and machine learning expertise. As a result, many social scientists do not apply them. This Element provides the working social scientist with an overview of the most common methods for text classification, an intuition of their applicability, and Python code to execute them. It covers both the ethical foundations of such work as well as the emerging potential of neural network methods. This Element provides the working social scientist with an overview of the most common methods for text classification, an intuition of their applicability, and Python code to execute them. It covers both the ethical foundations of such work as well as the emerging potential of neural network methods. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108819826 ISBN 13: 9781108819824
Language: English
Seller: CitiRetail, Stevenage, United Kingdom
US$ 35.38
Convert currencyQuantity: 1 available
Add to basketPaperback. Condition: new. Paperback. Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it. Text is a fantastic resource for social scientists, but because it is so abundant, and so variable, it can be difficult to extract the information we want. Many basic text analysis methods are available as Python implementations: this Element will teach you when to use which method, how it works, and the Python code to implement it. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.