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Text analytics with Pythona practiti...
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Sarkar, Dipanjan.
Text analytics with Pythona practitioner's guide to natural language processing /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Text analytics with Pythonby Dipanjan Sarkar.
Reminder of title:
a practitioner's guide to natural language processing /
Author:
Sarkar, Dipanjan.
Published:
Berkeley, CA :Apress :2019.
Description:
xxiv, 674 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Python (Computer program language)
Online resource:
https://doi.org/10.1007/978-1-4842-4354-1
ISBN:
9781484243541$q(electronic bk.)
Text analytics with Pythona practitioner's guide to natural language processing /
Sarkar, Dipanjan.
Text analytics with Python
a practitioner's guide to natural language processing /[electronic resource] :by Dipanjan Sarkar. - 2nd ed. - Berkeley, CA :Apress :2019. - xxiv, 674 p. :ill., digital ;24 cm.
Chapter 1: Natural Language Processing Basics -- Chapter 2: Python for Natural Language Processing -- Chapter 3: Processing and Understanding Text -- Chapter 4: Feature Engineering for Text Data -- Chapter 5: Text Classification -- Chapter 6: Text summarization and topic modeling -- Chapter 7: Text Clustering and Similarity analysis -- Chapter 8: Sentiment Analysis -- Chapter 9: Deep learning in NLP.
ISBN: 9781484243541$q(electronic bk.)
Standard No.: 10.1007/978-1-4842-4354-1doiSubjects--Topical Terms:
215247
Python (Computer program language)
LC Class. No.: QA76.73.P98 / S275 2019
Dewey Class. No.: 005.133
Text analytics with Pythona practitioner's guide to natural language processing /
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a practitioner's guide to natural language processing /
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by Dipanjan Sarkar.
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Chapter 1: Natural Language Processing Basics -- Chapter 2: Python for Natural Language Processing -- Chapter 3: Processing and Understanding Text -- Chapter 4: Feature Engineering for Text Data -- Chapter 5: Text Classification -- Chapter 6: Text summarization and topic modeling -- Chapter 7: Text Clustering and Similarity analysis -- Chapter 8: Sentiment Analysis -- Chapter 9: Deep learning in NLP.
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EB QA76.73.P98 S245 2019 2019
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https://doi.org/10.1007/978-1-4842-4354-1
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