Spelling Correction in Python with TextBlob
Spelling mistakes are common, and most people are used to software indicating if a mistake was made. From autocorrect on our phones, to red underlining in text editors, spell checking is an essential feature for many different products. The first program to implement spell checking was written in 1971 for...
Simple NLP in Python with TextBlob: N-Grams Detection
The constant growth of data on the Internet creates a demand for tools that process textual information. Moreover, it's highly important that this instrument of text analysis could implement solutions for both low and high-level NLP tasks such as counting word frequencies, calculating sentiment analysis of the texts or detecting...
Sentiment Analysis in Python With TextBlob
State-of-the-art technologies in NLP allow us to analyze natural languages on different layers: from simple segmentation of textual information to more sophisticated methods of sentiment categorizations. However, it does not inevitably mean that you should be highly advanced in programming to implement high-level tasks such as sentiment analysis in Python....
Simple NLP in Python With TextBlob: Tokenization
The amount of textual data on the Internet has significantly increased in the past decades. There's no doubt that the processing of this amount of information must be automated, and the TextBlob package is one of the fairly simple ways to perform NLP - Natural Language Processing. It provides a...