Natural Language Processing And Computational Linguistics A Practical Guide To Text Analysis With Pyt
User Manual:
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Page Count: 523 [warning: Documents this large are best viewed by clicking the View PDF Link!]
- Title Page
- Copyright and Credits
- Packt Upsell
- Contributors
- Preface
- What is Text Analysis?
- Python Tips for Text Analysis
- spaCy's Language Models
- Gensim – Vectorizing Text and Transformations and n-grams
- POS-Tagging and Its Applications
- NER-Tagging and Its Applications
- Dependency Parsing
- Topic Models
- Advanced Topic Modeling
- Clustering and Classifying Text
- Similarity Queries and Summarization
- Word2Vec, Doc2Vec, and Gensim
- Deep Learning for Text
- Keras and spaCy for Deep Learning
- Sentiment Analysis and ChatBots
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