MARC details
000 -LEADER |
fixed length control field |
02568cam a22003257i 4500 |
001 - CONTROL NUMBER |
control field |
10908 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
IN-BhIIT |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20240708113614.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
161125t20162016cau 001 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
ISBN |
9781484243534 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
IN-BhIIT |
041 ## - LANGUAGE CODE |
Language code of text |
eng |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
006.35 |
Book number |
SAR/T |
100 1# - MAIN ENTRY--AUTHOR NAME |
Personal name |
Sarkar, Dipanjan, |
Relator term |
Author. |
245 10 - TITLE STATEMENT |
Title |
Text analytics with python : |
Sub Title |
a practical real-world approach to gaining actionable insights from your data / |
Statement of responsibility, etc |
by Dipanjan Sarkar. |
250 ## - EDITION STATEMENT |
Edition statement |
2nd ed. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication |
Karnataka : |
Name of publisher |
Apress, |
Year of publication |
2019. |
300 ## - PHYSICAL DESCRIPTION |
Number of Pages |
xxiv, 674 p. ; |
Other physical details(ill.) |
ill. ; |
Dimensions(size) |
24 cm |
500 ## - GENERAL NOTE |
General note |
Text Analytics with Python is a comprehensive guide to utilizing Python for data analysis. It covers basic and advanced concepts of text and language syntax, structure, and semantics, as well as algorithms like text classification, clustering, topic modeling, and text summarization. The book is designed for IT professionals, analysts, developers, linguistic experts, and data scientists interested in linguistics, analytics, and generating insights from textual data. |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc |
Includes bibliographical references and index. |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Introduction -- Natural language basics -- Python refresher -- Processing and understanding text -- Text classification -- Text summarization -- Text similarity and clustering -- Semantic and sentiment analysis. |
520 ## - SUMMARY, ETC. |
Summary, etc |
The second edition of this book focuses on Natural Language Processing (NLP) in Python and how to set up a robust environment for text analytics. It introduces state-of-the-art frameworks in NLP, along with Machine Learning and Deep Learning, to solve real-world case studies. The book includes a dedicated chapter on Python for NLP, feature engineering representation methods, and techniques for parsing and processing text data. It also covers text classification, text summarization, text similarity techniques, sentiment analysis, machine learning and deep learning models, semantic analysis, and deep transfer learning. The book will be updated to the latest Python 3.x release, showcasing diverse NLP applications such as classification, clustering, similarity recommenders, topic models, sentiment and semantic analysis. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical Term |
Python (Computer program language) |
|
Topical Term |
Natural language processing (Computer science) |
|
Topical Term |
Natural language processing (Computer science) |
|
Topical Term |
Python (Computer program language) |
|
Topical Term |
Text Mining |
|
Topical Term |
Artificial intelligence. |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Koha item type |
Technical Reference Book |