Text Mining With Machine Learning

Download Text Mining With Machine Learning full books in PDF, epub, and Kindle. Read online free Text Mining With Machine Learning ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Text Mining with Machine Learning

Text Mining with Machine Learning
Author :
Publisher : CRC Press
Total Pages : 326
Release :
ISBN-10 : 9780429890260
ISBN-13 : 0429890265
Rating : 4/5 (265 Downloads)

Book Synopsis Text Mining with Machine Learning by : Jan Žižka

Download or read book Text Mining with Machine Learning written by Jan Žižka and published by CRC Press. This book was released on 2019-10-31 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various data sets, conclusions which are not normally evident, emerge and can be used for various purposes and applications. The book provides explanations of principles of time-proven machine learning algorithms applied in text mining together with step-by-step demonstrations of how to reveal the semantic contents in real-world datasets using the popular R-language with its implemented machine learning algorithms. The book is not only aimed at IT specialists, but is meant for a wider audience that needs to process big sets of text documents and has basic knowledge of the subject, e.g. e-mail service providers, online shoppers, librarians, etc. The book starts with an introduction to text-based natural language data processing and its goals and problems. It focuses on machine learning, presenting various algorithms with their use and possibilities, and reviews the positives and negatives. Beginning with the initial data pre-processing, a reader can follow the steps provided in the R-language including the subsuming of various available plug-ins into the resulting software tool. A big advantage is that R also contains many libraries implementing machine learning algorithms, so a reader can concentrate on the principal target without the need to implement the details of the algorithms her- or himself. To make sense of the results, the book also provides explanations of the algorithms, which supports the final evaluation and interpretation of the results. The examples are demonstrated using realworld data from commonly accessible Internet sources.


Text Mining with Machine Learning Related Books

Text Mining with Machine Learning
Language: en
Pages: 326
Authors: Jan Žižka
Categories: Computers
Type: BOOK - Published: 2019-10-31 - Publisher: CRC Press

DOWNLOAD EBOOK

This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various
Supervised Machine Learning for Text Analysis in R
Language: en
Pages: 402
Authors: Emil Hvitfeldt
Categories: Computers
Type: BOOK - Published: 2021-10-22 - Publisher: CRC Press

DOWNLOAD EBOOK

Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for
Machine Learning for Text
Language: en
Pages: 510
Authors: Charu C. Aggarwal
Categories: Computers
Type: BOOK - Published: 2018-03-19 - Publisher: Springer

DOWNLOAD EBOOK

Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully cov
Text Mining
Language: en
Pages: 222
Authors: Michael W. Berry
Categories: Mathematics
Type: BOOK - Published: 2010-02-25 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. The contributo
Mining Text Data
Language: en
Pages: 527
Authors: Charu C. Aggarwal
Categories: Computers
Type: BOOK - Published: 2012-02-03 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software te