Email_Spam_Detection

A ML Project for detecting the span in the e-mails.

📧 Email Spam Detection using Machine Learning

📌 Project Overview

This project is a Machine Learning-based Email Spam Classifier that detects whether an email is Spam or Not Spam (Ham). The model is trained using Natural Language Processing (NLP) techniques and classification algorithms.

 Features

• Preprocessing of email text (cleaning, tokenization, stopword removal)
• Feature extraction using TF-IDF (Term Frequency - Inverse Document Frequency)
• Classification using Naïve Bayes / Logistic Regression / Random Forest (mention what you used)
• Model evaluation using accuracy, precision, recall, and F1-score

 Technologies Used

• Python
• Scikit-Learn
• Pandas & NumPy
• NLTK
• Matplotlib & Seaborn
• Jupyter Notebook / Google Colab

 Dataset

The dataset used for training and testing contains labeled emails as Spam or Ham. It has been preprocessed to remove noise and irrelevant information.

 How to Run

1. Clone the repository:

   git clone https://github.com/ARYAKRI/Email_Spam_Detection.git

2. Install the dependencies:

   pip install -r requirements.txt

3. Run the notebook or script to train the model.

Results

The trained model achieved XX% accuracy (replace with actual performance metrics).

 Conclusion

This project demonstrates the use of NLP and ML techniques to classify emails effectively. Future improvements could include deep learning models like LSTMs for better accuracy.

 Contributing

If you'd like to improve this project, feel free to submit a pull request!

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