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Applied Natural Language Processing with Python

Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing

  • Book
  • © 2018

Overview

Authors:
  1. Taweh Beysolow II

    1. San Francisco, USA

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  • Covers NLP packages such as NLTK, gensim,and SpaCy
  • Approaches topics such as "topic modeling" and "text summarization" in a beginner-friendly manner
  • Explains how to ingest text data via web crawlers for use in deep learning NLP algorithms such as Word2Vec and Doc2Vec

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Table of contents (5 chapters)

  1. Front Matter

    Pages i-xv
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  2. What Is Natural Language Processing?

    • Taweh Beysolow II
    Pages 1-12

  3. Review of Deep Learning

    • Taweh Beysolow II
    Pages 13-42

  4. Working with Raw Text

    • Taweh Beysolow II
    Pages 43-75

  5. Topic Modeling and Word Embeddings

    • Taweh Beysolow II
    Pages 77-119

  6. Text Generation, Machine Translation, and Other Recurrent Language Modeling Tasks

    • Taweh Beysolow II
    Pages 121-143

  7. Back Matter

    Pages 145-150
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Keywords

About this book

Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms. 


Applied Natural Language Processing with Python starts with reviewing the necessary machine learning concepts before moving onto discussing various NLP problems. After reading this book, you will have the skills to apply these concepts in your own professional environment.





What You Will Learn  
  • Utilize various machine learning and natural language processing libraries such as TensorFlow, Keras, NLTK, and Gensim
  • Manipulate and preprocess raw text data in formats such as .txt and .pdf
  • Strengthen your skills in data science by learning both the theory and the application of various algorithms  



Who This Book Is For 


You should be at least a beginner in ML to get the most out of this text, but you needn’t feel that you need be an expert to understand the content.


Authors and Affiliations

  • San Francisco, USA

    Taweh Beysolow II

About the author

Taweh Beysolow II is a Machine Learning Scientist and Author currently based in the United States. He has a Bachelor of Science degree in Economics from St. Johns University and a Master of Science in Applied Statistics from Fordham University. His professional experience has included applying machine learning and natural language processing techniques to financial, text (structured and unstructured), and social media data. 

Bibliographic Information

  • Book Title: Applied Natural Language Processing with Python

  • Book Subtitle: Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing

  • Authors: Taweh Beysolow II

  • DOI: https://doi.org/10.1007/978-1-4842-3733-5

  • Publisher: Apress Berkeley, CA

  • eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)

  • Copyright Information: Taweh Beysolow II 2018

  • Softcover ISBN: 978-1-4842-3732-8Published: 12 September 2018

  • eBook ISBN: 978-1-4842-3733-5Published: 11 September 2018

  • Edition Number: 1

  • Number of Pages: XV, 150

  • Number of Illustrations: 32 b/w illustrations

  • Topics: Artificial Intelligence, Python, Open Source, Big Data

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