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The Natural Language Processing Workshop

You're reading from The Natural Language Processing Workshop Confidently design and build your own NLP projects with this easy-to-understand practical guide

Product type Paperback

Published in Aug 2020

Publisher Packt

ISBN-13 9781800208421

Length 452 pages

Edition 1st Edition

Languages

Processing

Tools

Jupyter

Concepts

Mobile Application Development

Authors (6):

Sohom Ghosh

Nipun Sadvilkar

Rohan Chopra

Muzaffar Bashir Shah

Dwight Gunning

Aniruddha M. Godbole

+2 more

View More author details

Table of Contents (10) Chapters

Preface

1. Introduction to Natural Language Processing

2. Feature Extraction Methods FREE CHAPTER

3. Developing a Text Classifier

4. Collecting Text Data with Web Scraping and APIs

5. Topic Modeling

6. Vector Representation

7. Text Generation and Summarization

8. Sentiment Analysis

Appendix

1. Introduction to Natural Language Processing

Overview

In this chapter, you will learn the difference between Natural Language Processing (NLP) and basic text analytics. You will implement various preprocessing tasks such as tokenization, lemmatization, stemming, stop word removal, and more. By the end of this chapter, you will have a deep understanding of the various phases of an NLP project, from data collection to model deployment.

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Authors (6)

Rohan Chopra

Rohan Chopra

Rohan Chopra graduated from Vellore Institute of Technology with a bachelors degree in computer science. Rohan has an experience of more than 2 years in designing, implementing, and optimizing end-to-end deep neural network systems. His research is centered around the use of deep learning to solve computer vision-related problems and has hands-on experience working on self-driving cars. He is a data scientist at Absolutdata.

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Muzaffar Bashir Shah

Muzaffar Bashir Shah

Muzaffar Bashir Shah is a software developer with vast experience in machine learning, natural language processing (NLP), text analytics, and data science. He holds a masters degree in computer science from the University of Kashmir and is currently working in a Bangalore based startup named Datoin.

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Nipun Sadvilkar

Nipun Sadvilkar

Nipun Sadvilkar is a senior data scientist at US healthcare company leading a team of data scientists and subject matter expertise to design and build the clinical NLP engine to revamp medical coding workflows, enhance coder efficiency, and accelerate revenue cycle. He has experience of more than 3 years in building NLP solutions and web-based data science platforms in the area of healthcare, finance, media, and psychology. His interests lie at the intersection of machine learning and software engineering with a fair understanding of the business domain. He is a member of the regional and national python community. He is author of pySBD - an NLP open-source python library for sentence segmentation which is recognized by ExplosionAI (spaCy) and AllenAI (scispaCy) organizations.

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Aniruddha M. Godbole

Aniruddha M. Godbole

Aniruddha M. Godbole is a data science consultant with inter-disciplinary expertise in computer science, applied statistics, and finance. He has a master's degree in data science from Indiana University, USA, and has done MBA in finance from the National Institute of Bank Management, India. He has authored papers in computer science and finance and has been an occasional opinion pages contributor to Mint, which is a leading business newspaper in India. He has fifteen years of experience.

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Dwight Gunning

Dwight Gunning

Dwight Gunning is a data scientist at FINRA, a financial services regulator in the US. He has extensive experience in Python-based machine learning and hands-on experience with the most popular NLP tools such as NLTK, gensim, and spacy.

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Sohom Ghosh

Sohom Ghosh

Sohom Ghosh is a passionate data detective with expertise in natural language processing. He has worked extensively in the data science arena with a specialization in deep learning-based text analytics, NLP, and recommendation systems. He has publications in several international conferences and journals.

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