GitHub repository: patrycas/How-to-identify-Spam-using-Natural-Language-Processing-NLP-
Primary language: Jupyter Notebook
Created: 2020-10-26T15:17:29Z
Description: The purpose of this article is to show you how to detect spam in SMS. For that, we use a dataset from the UCI datasets, which is a public set that contain SMS labelled messages that have been collected for mobile phone spam research. It has one collection composed by 5.574 SMS phone messages in English, tagged according being legitimate (ham) or spam.  Therefore, we will train a model to learn to automatically discriminate between ham / spam. Then we will use "test data" to test the model. and finally to evaluate if our model is efficient, we will calculate Accuracy, Classification report and Confusion Matrix.