Spam Email Classifier
A machine learning model that classifies emails as spam or not spam.
Spam Email Classifier
A machine learning model to classify emails as spam or not spam.
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Project Overview
This project focuses on classifying emails as spam or not spam using machine learning techniques. The goal is to build a model that can accurately distinguish between legitimate and spam emails based on features like word frequency, email structure, and metadata. The model was built using Python and Streamlit for visualization.
The Challenge
Classifying emails as spam or not spam is a complex task due to the variety of patterns and techniques used by spammers. The challenge was to build a model that could effectively identify spam emails while minimizing false positives.
Our Approach
We used a combination of data preprocessing, feature engineering, and machine learning algorithms to build a robust classification model. The dataset was cleaned and normalized, and we employed techniques like cross-validation to ensure the model's reliability and generalizability.
Technology Stack
Key Features
This project includes key features such as data preprocessing, model training, and visualization using Streamlit.