Spam SMS Detection using Machine Learning Project- Introduction

Spam SMS Detection using machine learning project:
SMS, standing for a short messaging service. SMS has become a dumping ground of unwanted product descriptions and scam offers. It is important to classify "spam" and "ham" sms. Classification using Machine Learning helps separating spam messages from ‘ham’ or legitimate messages. We used four simple classification models on a dataset from UCI Machine Learning Repository.
We used text classification using Naive Bayes.
This course Project conatins following videos:
1.Problem Statement - 9m
2.Importing Libraries and Data Set-15 m
• Spam SMS Detection usi...
3.Count Vectorization -6m
• Spam SMS Detection usi...
4.Preparing Data-3m
• Spam SMS Detection usi...
5.Model Training - 21m
• Spam SMS Detection usi...
Data Set Url: archive.ics.uc...