Introduction to Information Retrieval and Text Analytics
Information Retrieval and Text Analytics
by Daniel J. Taipala
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About the Book
To address the need for both theory and application, this book takes a slightly different approach as it takes reader on a fascinating journey that begins by learning basic principles of information retrieval and analytics. We then continue by exploring Hadoop, examining fundamental map-reduce algorithms implemented in python, and finally demonstrating how these concepts are applied with common use cases.
Features & Details
- Primary Category: Computers & Internet
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Project Option: 6×9 in, 15×23 cm
# of Pages: 352 -
Isbn
- Softcover: 9781364453107
- Publish Date: Jan 22, 2016
- Language English
- Keywords information, retrieval, big, data, hadoop, python, text, analytics, computer, science, machine, learning
About the Creator
Dr. Daniel Taipala is a scholar, educator, researcher, and practitioner holding roles in both the business and education domains. In the education domain Dr. Taipala is both educator and aministrator where he has served as both a professor of Computer Science and the Associate Dean for the Computer Science curriculum for the University of the People since 2010. Dan helped develop many of the computer science courses offered by the University of the People and has written two books that document the content taught in some of those courses. In addition Dr. Taipala is an Enterprise Architect and Distinguished Technologist who has been with the Hewlett Packard Enterprise company for more than 16 years where he has supported a number of fortune 100 global accounts. Dan’s specialty has been developing solutions to support global deployments for ERP (SAP, Oracle eBusiness), PLM, and MES/MOM, Cloud, and Big Data based solutions.