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OverviewFull Product DetailsAuthor: Mónica Bécue-BertautPublisher: Taylor & Francis Ltd Imprint: Chapman & Hall/CRC Weight: 0.312kg ISBN: 9781032093659ISBN 10: 103209365 Pages: 212 Publication Date: 30 June 2021 Audience: Professional and scholarly , General/trade , Professional & Vocational , General Format: Paperback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsEven though textual data science cannot be considered as the youngest sibling of other data science fields, there is still quite a big space to be filled with up-to-date textbooks describing and analyzing various methods and facets of this very interesting topic. In this book, Monica Becue-Bertaut tries to fill this gap, giving theoretical and practical instructions about one of the relatively little known, but powerful methods in textual data science-Correspondence Analysis (CA)... Extensive graphical images and visualizations represented by various types of plot and diagram are used throughout the material, which provides an even better aid to the reader for grasping the main ideas of the topic... separate mention should be drawn to the language used in the book. It is clear, simple, and even fun to read, providing an understandable way of covering complex topics... Monica Becue-Bertaut achieved a good blend of theory and practice in her book, which can be used as a handy resource for students and beginners in data science, as well as for specialists in textual data analysis. - Gia Jgarkava, ISCB December 2019 """Even though textual data science cannot be considered as the youngest sibling of other data science fields, there is still quite a big space to be filled with up-to-date textbooks describing and analyzing various methods and facets of this very interesting topic. In this book, Mónica Bécue-Bertaut tries to fill this gap, giving theoretical and practical instructions about one of the relatively little known, but powerful methods in textual data science–Correspondence Analysis (CA)... Extensive graphical images and visualizations represented by various types of plot and diagram are used throughout the material, which provides an even better aid to the reader for grasping the main ideas of the topic... separate mention should be drawn to the language used in the book. It is clear, simple, and even fun to read, providing an understandable way of covering complex topics... Mónica Bécue-Bertaut achieved a good blend of theory and practice in her book, which can be used as a handy resource for students and beginners in data science, as well as for specialists in textual data analysis."" - Gia Jgarkava, ISCB December 2019" Author InformationMónica Bécue-Bertaut is an elected fellow of the International Statistical Institute and was named Chevalier des Palmes Académiques by the French Government. She taught statistics and data science at the Universitat Politènica de Catalunya and offered numerous guest lectures on textual data science in different countries. Dr. Bécue-Bertaut published several books (in French or Spanish) and work chapters (in English) on this last topic. She also participated in the design of software related to textual data science, such as SPAD.T and Xplortext; being this latter an R package. Tab Content 6Author Website:Countries AvailableAll regions |