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Books About Python and NLP

Finding Books about Natural Language Processing

I thought I would spend a short moment to search for book and gather the descriptions of a few books on the topic of Python and different libraries.

I have the first book in my library. This list is in no specific order.

Natural Language Processing with Python (NLTK) (2009)

I was sent this book about that I assume is an excellent book from 2009. Being from 2009 does by no means make it a bad book, quite the contrary, I am sure there is much insight and interesting thoughts that have appeared in the original and the revisions. However, I found that I wanted to be working with spaCy as a package as opposed to NLTK that is represented in the book. It has an introduction to natural language processing (NLP), however it begins from an NLTK standpoint from the first section.

It has quite good reviews, but only two of those are from 2020.

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Natural Language Processing with Python and spaCy (2020)

  • Chapter 1: How Natural Language Processing Works
  • Chapter 2: The Text-Processing Pipeline
  • Chapter 3: Working with Container Objects and Customizing spaCy
  • Chapter 4: Extracting and Using Linguistic Features
  • Chapter 5: Working with Word Vectors
  • Chapter 6: Finding Patterns and Walking Dependency Trees
  • Chapter 7: Visualizations
  • Chapter 8: Intent Recognition
  • Chapter 9: Storing User Input in a Database
  • Chapter 10: Training Models
  • Chapter 11: Deploying Your Own Chatbot
  • Chapter 12: Implementing Web Data and Processing Images Linguistic Primer

Downside: it only has one review on Amazon and it is one star.

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Practical Natural Language Processing: A Comprehensive Guide to Building Real-World NLP Systems (2020)

With this book, you’ll:

  • Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP
  • Implement and evaluate different NLP applications using machine learning and deep learning methods
  • Fine-tune your NLP solution based on your business problem and industry vertical
  • Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages
  • Produce software solutions following best practices around release, deployment, and DevOps for NLP systems
  • Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective

Natural Language Processing in Action: Understanding, analyzing, and generating text with Python (2019)

AI Policy and Ethics at www.nora.ai. Student at University of Copenhagen MSc in Social Data Science. All views are my own. twitter.com/AlexMoltzau

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