Basics of Natural Language Processing
Which basically consists of combining machine learning techniques with text, and using math and statistics to get that text in a format that the machine learning algorithms can understand!
Model is made on SMSSpamCollection dataset which contains a collection of more than 5 thousand SMS phone messages.
Starting with pre-processeing like remove stopwords, Vectorization, Tfidf Transformer etc.
Training model with Multinomial Naive Bayes algorithm.
Checking for classification report.
Also Creating a Data Pipeline to store a pipeline of workflow.