SpamGuardian is a powerful Python-based project designed to detect spam messages using a robust Machine Learning model. With this tool, you can simply paste a message, and our AI will determine whether it's spam or not, helping you stay safe from unwanted and potentially harmful content.
- Streamlit: Used for rendering and deploying the application.
- NLTK: Natural Language Toolkit for text processing and analysis.
- Scikit-learn: Utilized for building and training the Machine Learning model.
- NumPy: Essential for numerical operations.
- Pandas: Efficient data manipulation and analysis.
- Data Cleaning: Ensured high-quality data by removing irrelevant information and handling missing values.
- EDA (Exploratory Data Analysis): Explored and visualized the dataset to gain insights into the distribution and characteristics of spam messages.
- Data Preprocessing: Prepared the data for model training by tokenizing, stemming, and vectorizing text data.
- Model Building: Employed machine learning techniques to build a robust spam detection model.
- Making PKL Files: Created Pickle files to efficiently use the trained model in the main application (app.py).
The application is deployed on Streamlit, providing an easy-to-use and interactive interface for users to check messages for spam.
- Visit the deployed application link.
- Paste the message you want to check into the provided text area.
- Click the "Check Spam" button.
- Receive instant feedback on whether the message is spam or not.
Stay safe from spam with SpamGuardian! 🛡️💬
To run SpamGuardian locally, follow these steps:
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Clone the repository:
git clone https://github.com/HimanshuMohanty-Git24/SpamGuardian.git
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Navigate to the project directory:
cd SpamGuardian -
Install the required Python libraries:
pip install -r requirements.txt
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Run the Streamlit application:
streamlit run app.py
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Open your web browser and go to
http:https://localhost:8501to access the SpamGuardian application.
We would like to express our gratitude to the open-source community and the developers behind the libraries used in this project.
This project is licensed under the MIT License.
Feel free to contribute and make SpamGuardian even better! 🚀👩💻👨💻