Spam-Email-Classification

E-Mail Spam Classification via Machine Learning and NLP

In this project, I developed a machine learning model for spam email classification using Natural Language Processing (NLP) and Machine Learning techniques. The goal of this project is to accurately classify emails as either spam or ham (non-spam) based on their content.

Project Overview:

• The project utilizes a dataset of emails, which are processed and vectorized using techniques like CountVectorizer.
• A Naive Bayes classifier is used for training the model, and it is then evaluated for its accuracy on test data.
• The final model can classify new email inputs, identifying whether they are spam or not.
• The project also includes a simple web application using Streamlit for real-time email classification.

Technologies Used:

• Python
• Pandas
• NumPy
• Scikit-learn
• Streamlit (for web app interface)