عنوان
پدید آورنده
موضوع
رده
QA76.9.N38 .S656 2018eb
QA76
.
9
.
N38
.
S656
2018eb
کتابخانه
محل استقرار
1788837037
178883853X
9781788837033
9781788838535
Natural Language Processing and Computational Linguistics :
[Book]
a Practical Guide to Text Analysis with Python, Gensim, SpaCy, and Keras.
Birmingham :
Packt Publishing Ltd,
2018.
1 online resource (298 pages)
Cover; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: What is Text Analysis?; What is text analysis?; Where's the data at?; Garbage in, garbage out; Why should you do text analysis?; Summary; References; Chapter 2: Python Tips for Text Analysis; Why Python?; Text manipulation in Python; Summary; References; Chapter 3: spaCy's Language Models; spaCy; Installation; Troubleshooting; Language models; Installing language models; Installation -- how and why?; Basic preprocessing with language models; Tokenizing text; Part-of-speech (POS) -- tagging.
Chapter 13: Deep Learning for TextDeep learning; Deep learning for text (and more); Generating text; Summary; References; Chapter 14: Keras and spaCy for Deep Learning; Keras and spaCy; Classification with Keras; Classification with spaCy; Summary; References; Chapter 15: Sentiment Analysis and ChatBots; Sentiment analysis; Reddit for mining data; Twitter for mining data; ChatBots; Summary; References; Other Books You May Enjoy; Index.
Exploring documentsTopic coherence and evaluating topic models; Visualizing topic models; Summary; References; Chapter 10: Clustering and Classifying Text; Clustering text; Starting clustering; K-means; Hierarchical clustering; Classifying text; Summary; References; Chapter 11: Similarity Queries and Summarization; Similarity metrics; Similarity queries; Summarizing text; Summary; References; Chapter 12: Word2Vec, Doc2Vec, and Gensim; Word2Vec; Using Word2Vec with Gensim; Doc2Vec; Other word embeddings; GloVe; FastText; WordRank; Varembed; Poincare; Summary; References.
Named entity recognitionRule-based matching; Preprocessing; Summary; References; Chapter 4: Gensim -- Vectorizing Text and Transformations and n-grams; Introducing Gensim; Vectors and why we need them; Bag-of-words; TF-IDF; Other representations; Vector transformations in Gensim; n-grams and some more preprocessing; Summary; References; Chapter 5: POS-Tagging and Its Applications; What is POS-tagging?; POS-tagging in Python; POS-tagging with spaCy; Training our own POS-taggers; POS-tagging code examples; Summary; References; Chapter 6: NER-Tagging and Its Applications; What is NER-tagging?
NER-tagging in PythonNER-tagging with spaCy; Training our own NER-taggers; NER-tagging examples and visualization; Summary; References; Chapter 7: Dependency Parsing; Dependency parsing; Dependency parsing in Python; Dependency parsing with spaCy; Training our dependency parsers; Summary; References; Chapter 8: Topic Models; What are topic models?; Topic models in Gensim; Latent Dirichlet allocation; Latent semantic indexing; Hierarchical Dirichlet process; Dynamic topic models; Topic models in scikit-learn; Summary; References; Chapter 9: Advanced Topic Modeling; Advanced training tips.
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Discover how you can perform your own modern text analysis, to make predictions, create inferences, and gain insights about the data around you today. Learn how to harness the powerful Python ecosystem and tools such as spaCy and Gensim to perform natural language processing, and computational linguistics algorithms.
01201872
B09470
Natural Language Processing and Computational Linguistics : A Practical Guide to Text Analysis with Python, Gensim, SpaCy, and Keras.
9781788838535
Computational linguistics.
Machine learning.
Natural language processing (Computer science)
Python (Computer program language)
Artificial intelligence.
Computational linguistics.
Computers-- Intelligence (AI) & Semantics.
Computers-- Natural Language Processing.
Computers-- Neural Networks.
Machine learning.
Natural language & machine translation.
Natural language processing (Computer science)
Neural networks & fuzzy systems.
Python (Computer program language)
006
.
35
QA76
.
9
.
N38
.
S656
2018eb
Srinivasa-Desikan, Bhargav.
20200823060505.0
pn
مطالعه متن کتاب [Book]
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