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Sentiment-Analysis-of-imdb-movie-reviews

NLP

In this repository, an issue in the field of natural language processing was addressed. This was a binary classification of positive or negative comments about IMDB movies.

In this case, pre-processing was done first. The most important of which was deleting the stop words and stemming. Then the words were vectorized using TFIDF method.

A number of different machine learning methods such as KNN, SVM, Random Forest Bayse and XGBoost were used to train the model. Finally, the results were evaluated using diffrent criterias.