This model classifies spam messages. from data, Spam messages have more average words than Ham messages. Spam messages have more average Punctuation than Ham messages.

describe what can people use it for, or how it makes existing tasks easier/safer e.t.c (markdown supported)

The problem it solves

This is one of the guided projects. So, not needed to head around much. I used CountVectorizer for feature extraction of the text data(i.e., SMSs) with hyperparameters such as lowercase(which converts the text into a lowercase test) and stop_words(which, removes all the stop words from the text data)

SMS Spam Classifier

I built this spam classifier model using a Support Vector Machine classifier. The dataset used was taken from Kaggle.com

The problem SMS Spam Classifier solves

Challenges I ran into