NLP Tokenization & Regular Expressions in Python

Course outline

Tokenization & Regular Expressions:-

- Overview of Tokenization

- Linguistic theory for Word Segmentation

- Tokenization with NLTK

- Cliticisation & Contractions in Tokenization

- Contractions Library

- Overview of Regular Expressions

- Word Segmentation

- Sentence Segmentation

- ReGex Split & Subsitute Method

- Search Method

Prerequisite knowledge

Python Programming Knowledge

Basic Natural Language Processing (NLP) Knowledge

Learning outcomes

This micro-learning session will take the learners through NLP techniques, Tokenization and Regular Expression, for parsing text.

Software / Hardware requirements

Anaconda Distribution

Install the ‘64-bit Graphical installer’

Python

(For both Windows & macOS)

Sugggested link:

https://www.anaconda.com/products/individual

Natural Language Processing (NLP) - Stemming & Lemmatization

1.25 hours session

Natural Language Processing (NLP) - Text Summarization

1.25 hours session

Deep Learning - Natural Language Processing (NLP)

3 hours session

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