Overview / Usage

In this project, the system justify that we can build platform to classify news on dynamic data set of news corpus on broad range of topics.

News articles were crawled from news website using scarpy to generate the training data for supervised learning. Stemming, tokenization and POS tagging under NLP were implemented along Naive Bayes classifier and IF-IDF classifier as machine learning approaches in order to classify the news corpse. Finally the classified news were interpreted and the information were visualize in the form of bar graphs and pie-chart.