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The Natural Language Processing Workshop

You're reading from The Natural Language Processing Workshop

Product type Book

Published in Aug 2020

Publisher Packt

ISBN-13 9781800208421

Pages 452 pages

Edition 1st Edition

Languages

Concepts

Mobile Application Development

Authors (6):

Rohan Chopra

Aniruddha M. Godbole

Nipun Sadvilkar

Muzaffar Bashir Shah

Sohom Ghosh

Dwight Gunning

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Table of Contents (10) Chapters

Preface

1. Introduction to Natural Language Processing

2. Feature Extraction Methods

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

Introduction

In the last chapter, we developed a simple classifier using feature extraction methods. We also covered different algorithms that fall under supervised and unsupervised learning. In this chapter, you will learn how to collect text data by scraping web pages, and then you will learn how to process that data. Web scraping helps you extract useful data from online content, such as product prices and customer reviews, which can then be used for market research, price comparison for products, or data analysis. You will also learn how to handle various kinds of semi-structured data, such as JSON and XML. We will cover different methods for extracting data using Application Programming Interfaces (APIs). Finally, we will explore different ways to extract data from different types of files.

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Authors (6)

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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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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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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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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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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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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