Supervised machine learning using a data set of 2500 ham and 500 spam emails. Data is also split into train and test sets of various sizes to test the classifier's efficiency. (Python)
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Updated
Dec 17, 2017 - Jupyter Notebook
Supervised machine learning using a data set of 2500 ham and 500 spam emails. Data is also split into train and test sets of various sizes to test the classifier's efficiency. (Python)
ML-powered Flask app to perform spam classification of SMS messages.
It is based on support vector machines ,first we used linear kernel for lesser featured dataset, Gaussian kernel for more complex dataset.
Python program that classifies spam using Bayes theorem
Spam classifier using Naive Bayes.
NO SPAM is a Spam-Sms-Classifier tool designed to accurately classify text messages as either spam or not spam. Using advanced machine learning algorithms, the classifier analyzes the content of SMS messages and determines their likelihood of being unsolicited or unwanted.
A Spam Classifier using Naive Bayes
ML - Support Vector Machines + Spam Classifier - Python
IF4072 Natural Language & Text Processing
IF4072 Natural Language & Text Processing
Naive Bayes Spam Classifier
Spam classifier using support vector machine (LIBSVM)
A simple email spam classifier (Python)
In this project I perform a simple spam detection task over the SMS Spam Collection Data Set (https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection).
Built a spam classifier from the UCI Spambase data set
In this project I build an end-to-end sms spam classifier and hosted it on Streamlit cloud.
This web app is powered with ML, NLP which identifies whether the message is a spam or not.
A simple spam classifier built with Bayes' theorem.
Artificial Intelligence Project
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