Text Classification is a process of classifying data in the form of text such as tweets, reviews, articles, and blogs, into predefined categories. Sentiment analysis is a special case of Text Classification where users’ opinion or sentiments about any product are predicted from textual data.
In this tutorial, you will learn how to develop a Sentiment Analysis model that will use TF-IDF feature generation approach and will be capable of predicting user sentiment (i.e. view or opinion that is held or expressed) about 6 Airlines operating in the United States through analysing user tweets. You will use Python’s Scikit-Learn library for machine learning to implement the TF-IDF approach and to train our prediction model.
I am Machine Learning and Data Science expert currently pursuing my PhD in Computer Science from Normandy University, France.