Email spam predictor

In this machine learning model , we are detecting the spam in email inbox. We are making use of the Natural Language Processing toolkit libraries. At first, we are importing all libraries and visualising the given dataset. Then we are processing the dataset and have downloaded the 'stopwords' package and then cleaning the data. Then we convert the text into a matrix and split the dataset into training and testing set. Then we create a Naive Bayes classifier and make predictions on our model. At the end we predict the accuracy of the training set and testing set of the model.

Built With

• jupyter
• natural-language-processing
• python