Add spam mail prediction

[SayantikaLaskar]

Issue #204

Spam emails are a significant issue for many users, leading to wasted time and potential security threats. Our project leverages machine learning techniques to identify and filter out spam emails. The model will be trained on a labeled dataset of emails and will use various features extracted from the email content and metadata.

Features

• Email Preprocessing: Clean and preprocess email data for model training.
• Feature Extraction: Extract relevant features from emails, such as word frequency, email headers, and metadata.
• Model Training: Train a machine learning model using the preprocessed and feature-extracted data.
• Spam Detection: Classify new emails as spam or not spam using the trained model.
• Evaluation Metrics: Evaluate the performance of the model using accuracy, precision, recall, and F1-score.