CS3244 project - worked on SMS spam classifier using KNN
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Updated
Aug 6, 2019 - Python
CS3244 project - worked on SMS spam classifier using KNN
A machine learning project using different feature analysis and cross validation and NLP.
High-performance SMS spam detection using a scalable Naive Bayes algorithm and Hadoop's MapReduce framework to tackle large-scale spam filtering effectively.
SMS Spam and Ham Detection using Multinomial Naive Bayes Algorithm.
An interactive SMS Spam Detection application using Streamlit and machine learning. This app allows users to classify messages as spam or ham and view performance metrics for different models.
SMS Spam Collection Data Set
Simple example for Kaggles SMS Spam Collection Dataset with a simple LSTM.
Natural Language Processing using Tensorflow, the model is trained on >5000 SMS text messages to identify spam messages with an validation accuracy of over 98%.
Use the Naive Bayes algorithm to create a model that can classify dataset (https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection) SMS messages as spam or not spam
detects youtube comment spam, text spam, email spam, sms spam in one
New ! Best iranian SMS bomber..(2024)
Spam classifier using Bag of Words (BOW) model and Support Vector Machine (SVM) applied with GridSearchCV.
Birden Fazla Sms Atarak İstediğiniz Kişiye Şaka Yapabilirsiniz.
SMS Spam Detection using Machine Learning Approach
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