Spam Mail Prediction using Machine Learning with Python

Overview

This project aims to predict whether an email is spam or not using machine learning techniques. The SpamMailPrediction.ipynb Jupyter notebook contains the code and analysis required to build, train, and evaluate a spam mail classification model.

Files

• SpamMailPrediction.ipynb: Jupyter notebook containing the entire workflow for spam mail prediction.

Features

• Data preprocessing and cleaning
• Feature extraction
• Model training using machine learning algorithms
• Evaluation of model performance
• Predictions on new data

Requirements

To run the notebook, you'll need:

• Python 3.x

• Jupyter Notebook

• Libraries: pandas, numpy, scikit-learn, matplotlib, seaborn

  Create a requirements.txt file with the following content:

Running the Notebook

Open the Jupyter notebook with:

SpamMailPrediction.ipynb

Then, install the dependencies using:

pip install -r requirements.txt