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....
Python for NLP: Tokenization, Stemming, and Lemmatization with SpaCy Library
In the previous article, we started our discussion about how to do natural language processing with Python. We saw how to read and write text and PDF files. In this article, we will start working with the spaCy library to perform a few more basic NLP tasks such as tokenization,...
Implementing Word2Vec with Gensim Library in Python
Humans have a natural ability to understand what other people are saying and what to say in response. This ability is developed by consistently interacting with other people and the society over many years. The language plays a very important role in how humans interact. Languages that humans use for...
Text Summarization with NLTK in Python
As I write this article, 1,907,223,370 websites are active on the internet and 2,722,460 emails are being sent per second. This is an unbelievably huge amount of data. It is impossible for a user to get insights from such huge volumes of data. Furthermore, a...