000 | 02568cam a22003257i 4500 | ||
---|---|---|---|
001 | 10908 | ||
003 | IN-BhIIT | ||
005 | 20240708113614.0 | ||
008 | 161125t20162016cau 001 0 eng d | ||
020 | _a9781484243534 | ||
040 | _aIN-BhIIT | ||
041 | _aeng | ||
082 | 0 | 4 |
_a006.35 _bSAR/T |
100 | 1 |
_aSarkar, Dipanjan, _eAuthor. _923732 |
|
245 | 1 | 0 |
_aText analytics with python : _ba practical real-world approach to gaining actionable insights from your data / _cby Dipanjan Sarkar. |
250 | _a2nd ed. | ||
260 |
_aKarnataka : _bApress, _c2019. |
||
300 |
_axxiv, 674 p. ; _bill. ; _c24 cm |
||
500 | _aText 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 | _aIncludes bibliographical references and index. | ||
505 | 0 | _aIntroduction -- Natural language basics -- Python refresher -- Processing and understanding text -- Text classification -- Text summarization -- Text similarity and clustering -- Semantic and sentiment analysis. | |
520 | _aThe 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 |
_aPython (Computer program language) _92578 |
|
650 | 0 |
_aNatural language processing (Computer science) _922172 |
|
650 | 7 |
_aNatural language processing (Computer science) _922172 |
|
650 | 7 |
_aPython (Computer program language) _92578 |
|
650 | 7 |
_aText Mining _923733 |
|
650 | 7 |
_aArtificial intelligence. _9739 |
|
942 | _cTRB | ||
999 |
_c13898 _d13898 |