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SMS_Spam_Classification

SMS_Spam_Classification uses Natural Language Processing techniques of text preprocessing(noise removal, tokenization & stemmation), feature engineering and TF-IDF vectorizer to classify SMS into spams and hams. It uses Gaussian Naive Bayes, Logistics Regression, XGBoost, Random Forest ensemble & rbf kernel SVM to create ML models and check the accuracy for each model created.

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A basic project on spam & ham classification using Natural Language Processing.

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