Tokenization

Given a text sequence, tokenization is the task of breaking it into fragments, which can be words, characters, or sentences. Sometimes, certain characters are usually removed, such as punctuation marks, digits, and emoticons. These fragments are the so-called tokens used for further processing. Moreover, tokens composed of one word are also called unigrams in computational linguistics; bigrams are composed of two consecutive words; trigrams of three consecutive words; and n-grams of n consecutive words. Here is an example of tokenization:

We can implement word-based tokenization using the word_tokenize function in NLTK. We will ...

Get Python Machine Learning By Example - Second Edition now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.