The main goal of this project is to classify the newsgroups dataset accurately into correct groups.
The dataset is a collection of approximately 20,000 newsgroup documents, partitioned (nearly) evenly across 20 different newsgroups.
At the first step, I Preprocessed the data and extracted the features of texts using the scikit-learn library, and then, I implemented the Multinomial Naive Bayes classifier (from the scikit-learn library) for classifying news into appropriate groups.
The accuracy score has calculated at the end to evaluate the model.