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Natural Language Processing with Python Quick Start Guide

You're reading from Natural Language Processing with Python Quick Start Guide Going from a Python developer to an effective Natural Language Processing Engineer

Product type Paperback

Published in Nov 2018

Publisher Packt

ISBN-13 9781789130386

Length 182 pages

Edition 1st Edition

Languages

Processing

Tools

Processing

Concepts

Mobile Application Development

Author (1):

Kasliwal

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Table of Contents (10) Chapters

Preface

1. Getting Started with Text Classification FREE CHAPTER

2. Tidying your Text

3. Leveraging Linguistics

4. Text Representations - Words to Numbers

5. Modern Methods for Classification

6. Deep Learning for NLP

7. Building your Own Chatbot

8. Web Deployments

9. Other Books You May Enjoy

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spaCy compared with NLTK and CoreNLP

The following is a comparison of the NLTK and CoreNLP:

Feature	Spacy	NLTK	CoreNLP
Native Python support/API	Y	Y	Y
Multi-language support	Y	Y	Y
Tokenization	Y	Y	Y
Part-of-speech tagging	Y	Y	Y
Sentence segmentation	Y	Y	Y
Dependency parsing	Y	N	Y
Entity recognition	Y	Y	Y
Integrated word vectors	Y	N	N
Sentiment analysis	Y	Y	Y
Coreference resolution	N	N	Y

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Authors (1)

Kasliwal

Kasliwal

Nirant Kasliwal maintains an awesome list of NLP natural language processing resources. GitHub's machine learning collection features this as the go-to guide. Nobel Laureate Dr. Paul Romer found his programming notes on Jupyter Notebooks helpful. Nirant won the first ever NLP Google Kaggle Kernel Award. At Soroco, image segmentation and intent categorization are the challenges he works with. His state-of-the-art language modeling results are available as Hindi2vec.

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