Text Analytics for Business Decisions
Text Analytics for Business Decisions
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Text Analytics for Business Decisions by Andres Fortino
With the rise in data science development, we now have many remarkable techniques and tools to extend data analysis from numeric and categorical data to textual data. Sifting through the open-ended responses from a survey, for example, was an arduous process when performed by hand. Using a case study approach, this book was written for business analysts who wish to increase their skills in extracting answers for text data in order to support business decision making. Most of the exercises use Excel, today's most common analysis tool, and R, a popular analytic computer environment. The techniques covered range from the most basic text analytics, such as key word analysis, to more sophisticated techniques, such as topic extraction and text similarity scoring. Companion files with numerous datasets are included for use with case studies and exercises. FEATURES:- Organized by tool or technique, with the basic techniques presented first and the more sophisticated techniques presented later
- Uses Excel and R for datasets in case studies and exercises
- Features the CRISP-DM data mining standard with early chapters for conducting the preparatory steps in data mining
- Companion files with numerous datasets and figures from the text.
The companion files are available online by emailing the publisher with proof of purchase at info@merclearning.com.
With the rise in data science development, we now have many remarkable techniques and tools to extend data analysis from numeric and categorical data to textual data. Sifting through the open-ended responses from a survey, for example, was an arduous process when performed by hand. Using a case study approach, this book was written for business analysts who wish to increase their skills in extracting answers for text data in order to support business decision making. Most of the exercises use Excel, today's most common analysis tool, and R, a popular analytic computer environment. The techniques covered range from the most basic text analytics, such as key word analysis, to more sophisticated techniques, such as topic extraction and text similarity scoring. Companion files with numerous datasets are included for use with case studies and exercises.
FEATURES:- Organized by tool or technique, with the basic techniques presented first and the more sophisticated techniques presented later
- Uses Excel and R for datasets in case studies and exercises
- Features the CRISP-DM data mining standard with early chapters for conducting the preparatory steps in data mining
- Companion files with numerous datasets and figures from the text.
The companion files are available online by emailing the publisher with proof of purchase at info@merclearning.com.
| SKU | Non disponible |
| ISBN 13 | 9781683926665 |
| ISBN 10 | 1683926668 |
| Titre | Text Analytics for Business Decisions |
| Auteur | Andres Fortino |
| État | Non disponible |
| Type de reliure | Paperback |
| Éditeur | Mercury Learning & Information |
| Année de publication | 2021-06-11 |
| Nombre de pages | 318 |
| Note de couverture | La photo du livre est présentée à titre d'illustration uniquement. La reliure, la couverture ou l'édition réelle peuvent varier. |
| Note | Non disponible |