TextBlob Spelling Correction

TextBlob Spelling Correction

TextBlob is a Python library for processing textual data. It provides a consistent API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, and more. NLU is a subset of NLP in which an unstructured data or sentence is being converted into its structured form for performing NLP in terms of handling end to end interactions.

What is TextBlob?

TextBlob is a Python library for processing textual data. It provides a consistent API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, and more.

Why TextBlob?

NLU is a subset of NLP in which an unstructured data or sentence is being converted into its structured form for performing NLP in terms of handling end to end interactions. Relation extraction, semantic parsing, sentiment analysis, Noun phrase extraction are few examples of NLU which itself is a subset of NLP. Now to work in these areas, TextBlob plays a great role which is not that efficiently done by NLTK.

Spelling Correction with TextBlob

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Photo by Romain Vignes on Unsplash

STEP: 1 → Installing TextBlob

Sometimes tweets, reviews, or any blog data may contain typo errors, hence first we need to correct that data to reducing multiple copies of the same words, which represents the same meaning.

Installing TextBlob on your computer is very simple. You simply need to install it using pip.

STEP: 2 → Load the Input for preprocessing

Just we have to feed the computer from the basics so that it can be very well trained in natural language understanding and processing.

Next, load the input text (as docx) for which you need the correct the spelling, and the text we are about to handle is Immigrants in Toronto.

text-analytics spell-check textblob nlp

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