SMS Spam Detection Using Machine Learning, Flask and Flutter

SMS Spam Detection Using Machine Learning, Flask and Flutter

Akshay Sable ^*1, Nilesh Urkude^*1, Vaibhav Bhade^*1, Shubham Dongare^*1,

 Chetan Morey^*1

  ^*1 Computer Science And Engineering, P.R.Pote College Of Engineering and Management , Amravati Maharashtra, India.

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Abstract – ML is termed as Machine Learning; it is the study of computer algorithms which automatically improves through experience. The usage of mobile phones is growing popular in our everyday life. Short Message Service are viewed as most generally applied correspondence administration which is less costly. In any case, this has prompted an increment in cell phones assaults like SMS Spam. Here, Naive bayes algorithm is used in order to differentiate between spam and ham SMS. Spam is the unnecessary fraud messages received whereas ham is legitimate message. The algorithm used here is machine learning classification algorithm, and it is implemented here and can be used in differentiating between spam and ham messages with the help of SMS spam collection data set provided. We train the machine by providing that data set such that it learns from that data and will be able to draw conclusions on its own. Now a days it is very much crucial to identify the spam messages to reduce many frauds happening around the globe. This algorithm can classify with an accuracy of 98.13%.

Keywords: Machine Learning, SMS Spam, Naïve Bayes Classifier, text classification, Sms Spam Detection App, Flutter and Python.