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This is a SMS Spam Detection Project with Streamlit
One of the primary methods for spam mail detection is email filtering. It involves categorize incoming emails into spam and non-spam. Machine learning algorithms can be trained to filter out spam mails based on their content and metadata.
Natural Language Processing
In this project we are using LSTM to classify texts as spam or ham.
Classification for SMS Spam Collection Dataset using BERT
Spam Classification using Naive Bayes Classifier
Welcome to the "SMS Spam Detector" project! This machine learning model identifies whether a given SMS is spam or not, providing a valuable tool for spam detection and filtering.
In this project, concepts of Natural Language Processing were used with the help of various Classification algorithms. The output will be classified as Spam or Ham.
An SMS spam classifier that can classify a message into Spam or Ham
This Project it's based on an Sms Spam Classifier that wil be to detect message is spam or ham.
An SMS spam classifier made using Naive Bayes classification algorithm on R
SMS and Email Spam Classifier end-to-end project, deployed on Streamlit