ML_Message_Classification

This repository explores the use of machine learning algorithms to classify messages and emails as 'Spam' or 'Not Spam'. It includes two distinct implementations:

1. spam_ham_1: Utilizes supervised learning techniques with labeled data to train and evaluate models.
2. spam_ham_2: Explores unsupervised learning approaches, working with unlabeled data to identify patterns and classify messages effectively.

All required datasets are stored in the data_file directory, containing the CSV files used for training and evaluation.

This repository serves as a comprehensive guide to spam detection using both supervised and unsupervised learning techniques