https://github.com/abhi227070/email-spam-detection
Email Spam Classifier: A real-time project that utilizes natural language processing (NLP), data analytics, and machine learning (ML) techniques to classify emails as spam or legitimate based on their text content.
https://github.com/abhi227070/email-spam-detection
deep-learning machine-learning machine-learning-algorithms natural-language-processing nlp-machine-learning python-programming streamlit-webapp
Last synced: 4 months ago
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Email Spam Classifier: A real-time project that utilizes natural language processing (NLP), data analytics, and machine learning (ML) techniques to classify emails as spam or legitimate based on their text content.
- Host: GitHub
- URL: https://github.com/abhi227070/email-spam-detection
- Owner: abhi227070
- Created: 2023-06-08T18:48:41.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-03-26T09:19:15.000Z (over 1 year ago)
- Last Synced: 2024-03-26T10:28:50.932Z (over 1 year ago)
- Topics: deep-learning, machine-learning, machine-learning-algorithms, natural-language-processing, nlp-machine-learning, python-programming, streamlit-webapp
- Language: Jupyter Notebook
- Homepage: https://abhi227070-email-spam-detection-app-29b78i.streamlit.app/
- Size: 665 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Email Spam Classifier
Classify emails as spam or legitimate in real-time using natural language processing (NLP), data analytics, and machine learning (ML) techniques.
## Table of Contents
- [Introduction](#introduction)
- [Technologies/Tools Used](#technologies-tools-used)
- [Description](#description)
- [Installation](#installation)
- [Usage](#usage)
- [Screenshots](#screenshots)
- [Contributing](#contributing)
- [License](#license)
## Introduction
Email Spam Classifier is a real-time project designed to classify emails as spam or legitimate based on their text content. By leveraging NLP and ML algorithms, the classifier provides efficient and accurate results, helping users filter out unwanted emails effectively.
## Technologies/Tools Used
- Streamlit
- NLTK
- Pickle
- Python
- Scikit-Learn
## Description
This project utilizes a trained machine learning model to classify emails. The text entered by the user is preprocessed to remove stopwords, punctuation, and non-alphanumeric characters. It is then transformed using TF-IDF vectorization before being passed to the model for prediction. The model predicts whether the email is spam or not, and the result is displayed in real-time.
## Installation
1. Clone the repository:
```bash
git clone https://github.com/your_username/email-spam-classifier.git
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
## Usage
1. Run the Streamlit web application:
```bash
streamlit run app.py
```
2. Enter the email text in the provided text area.
3. Click the "Predict" button to classify the email as spam or legitimate.
## Screenshots
## Contributing
Contributions are welcome! Please fork the repository and create a pull request with your proposed changes.
## License
This project is licensed under the [MIT License](LICENSE).