Following libraries have been used in this Natural Language Processing project: pandas for loading and exploring the dataset; NLTK and re for Data cleaning & preprocessing; TfidVectorizer from scikit-learn for vectorizing text; MultinomialNB from scikit-learn for Model Training; accuracy_score, classification_report & confusion_matrix from sklearn
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Following libraries have been used in this Natural Language Processing project: pandas for loading and exploring the dataset; NLTK and re for Data cleaning & preprocessing; TfidVectorizer from scikit-learn for vectorizing text; MultinomialNB from scikit-learn for Model Training; accuracy_score, classification_report & confusion_matrix from sklearn
meetk5/sentiment-analysis
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Following libraries have been used in this Natural Language Processing project: pandas for loading and exploring the dataset; NLTK and re for Data cleaning & preprocessing; TfidVectorizer from scikit-learn for vectorizing text; MultinomialNB from scikit-learn for Model Training; accuracy_score, classification_report & confusion_matrix from sklearn
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