In this project we will be creating a Fake news classifier model that will classify the news based on the 'title' and 'text' (separate jupyter notebooks), whether it is 'Real' or 'Fake'. The dataset that we are using here is taken from www.kaggle.com and comprises of following features Id, Title, Author, Text and Label. Firstly we will preprocess the text data by using stemming and stopwords followed by using Bag of Words and TFIDF (separate jupyter notebooks) to convert text into vectors. Finally creating models and evaluating their performances.
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In this project, we will be creating a Fake news classifier model that will classify the news based on the 'title' and 'text', whether it is 'Real' or 'Fake'. The dataset that we are using here is taken from www.kaggle.com.
prankur16shukla/Fake_News_Classifier
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In this project, we will be creating a Fake news classifier model that will classify the news based on the 'title' and 'text', whether it is 'Real' or 'Fake'. The dataset that we are using here is taken from www.kaggle.com.
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