E-book details

Natural Language Processing and Computational Linguistics. A practical guide to text analysis with Python, Gensim, spaCy, and Keras

Natural Language Processing and Computational Linguistics. A practical guide to text analysis with Python, Gensim, spaCy, and Keras

Bhargav Srinivasa-Desikan

Ebook
Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data.

This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy.

You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning.

This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis.
  • 1. What is Text Analysis?
  • 2. Python Tips for Text Analysis
  • 3. spaCy’s Language Models
  • 4. Gensim – Vectorizing text and transformations and n-grams
  • 5. POS-Tagging and its Applications
  • 6. NER-Tagging and its Applications
  • 7. Dependency Parsing
  • 8. Top Models
  • 9. Advanced Topic Modelling
  • 10. Clustering and Classifying Text
  • 11. Similarity Queries and Summarization
  • 12. Word2Vec, Doc2Vec and Gensim
  • 13. Deep Learning for text
  • 14. Keras and spaCy for Deep Learning
  • 15. Sentiment Analysis and ChatBots
  • Title: Natural Language Processing and Computational Linguistics. A practical guide to text analysis with Python, Gensim, spaCy, and Keras
  • Author: Bhargav Srinivasa-Desikan
  • Original title: Natural Language Processing and Computational Linguistics. A practical guide to text analysis with Python, Gensim, spaCy, and Keras
  • ISBN: 9781788837033, 9781788837033
  • Date of issue: 2018-06-29
  • Format: Ebook
  • Item ID: e_14yk
  • Publisher: Packt Publishing