Text Processing Using NLTK in Python [Video]

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Text Processing Using NLTK in Python [Video]

Krishna Bhavsar, Naresh Kumar, Pratap Dangeti

Monday, April 30, 2018

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Learn the tricks and tips that will help you design Text Analytics solutions

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Video Details

ISBN 139781789348989

Course Length1 hour and 24 minutes

Video Description

Natural Language Processing (NLP) is a feature of Artificial Intelligence concerned with the interactions between computers and human (natural) languages. This course includes unique videos that will teach you various aspects of performing Natural Language Processing with NLTK—the leading Python platform for the task.

In this course, you will learn what WordNet is and explore its features and usage. It will teach how to extract raw text from web sources and introduce some critical pre-processing steps. You will also get familiarized with the concept of pattern matching as a way to do text analysis.

By the end of the course, you will be confident & have covered various solutions, covering natural language understanding, Natural Language Processing, and syntactic analysis.

All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/Text-Processing-using-NLTK-in-Python

Style and Approach

This video course takes a solution-based approach where every topic is explicated with the help of a real-world example.

Corpus and WordNet

The Course Overview

Accessing In-Built Corpora

Downloading an External Corpus

Counting All the wh-words

Frequency Distribution Operations

WordNet

The Concepts of Hyponyms and Hypernyms Using WordNet

Compute the Average Polysemy According to WordNet

Raw Text, Sourcing, and Normalization

The Importance of String Operations

Getting Deeper with String Operations

Reading a PDF File in Python

Reading Word Documents in Python

Creating a User-Defined Corpus

Reading Contents from an RSS Feed

HTML Parsing Using BeautifulSoup

Pre-Processing

Tokenization – Learning to Use the Inbuilt Tokenizers of NLTK

Stemming – Learning to Use the Inbuilt Stemmers of NLTK

Lemmatization – Learning to Use the WordNetLemmatizer of NLTK

Stopwords – Learning to Use the Stopwords Corpus

Edit Distance – Writing Your Own Algorithm to Find Edit Distance Between Two Strings

Processing Two Short Stories and Extracting the Common Vocabulary

Regular Expressions

Regular Expression – Learning to Use *, +, and ?

Regular Expression – Learning to Use Non-Start and Non-End of Word

Searching Multiple Literal Strings and Substrings Occurrences

Creating Date Regex

Making Abbreviations

Learning to Write Your Own Regex Tokenizer

Learning to Write Your Own Regex Stemmer

What You Will Learn

Import, access external corpus & explore frequency distribution of the text in corpus file
Learn WordNet usage and a couple of simple application assignments using WordNet
Read word & text files and create user-defined corpus
Learn HTML parsing using BeautifulSoup
Perform tokenization, stemming, lemmatization, spelling corrections, stop words removals, and more
Understand Regular expressions for character matching
Write your own Regex tokenizer & stemmer using RNNs

Authors

Krishna Bhavsar

Krishna Bhavsar has spent around 10 years working on natural language processing, social media analytics, and text mining in various industry domains such as hospitality, banking, healthcare, and more. He has worked on many different NLP libraries such as Stanford CoreNLP, IBM's SystemText and BigInsights, GATE, and NLTK to solve industry problems related to textual analysis. He has also worked on analyzing social media responses for popular television shows and popular retail brands and products. He has also published a paper on sentiment analysis augmentation techniques in 2010 NAACL. he recently created an NLP pipeline/toolset and open sourced it for public use. Apart from academics and technology, Krishna has a passion for motorcycles and football. In his free time, he likes to travel and explore. He has gone on pan-India road trips on his motorcycle and backpacking trips across most of the countries in South East Asia and Europe.

Naresh Kumar

Naresh Kumar has more than a decade of professional experience in designing, implementing, and running very-large-scale Internet applications in Fortune Top 500 companies. He is a full-stack architect with hands-on experience in domains such as ecommerce, web hosting, healthcare, big data and analytics, data streaming, advertising, and databases. He believes in open source and contributes to it actively. Naresh keeps himself up-to-date with emerging technologies, from Linux systems internals to frontend technologies. He studied in BITS-Pilani, Rajasthan with dual degree in computer science and economics.