SMS/Email Spam Classifier 📧🚫

Developed a powerful ML model for classifying SMS/emails as spam or legitimate using advanced Vectorization and Natural Language Processing (NLP) techniques. The application is built using Streamlit for a user-friendly experience.

Key Achievements

• High Accuracy: Achieved an outstanding accuracy score of 0.98.
• Precision: Boasted a precision score of 0.991, showcasing the model's reliability.
• Technology Stack: Utilized Scikit-learn, Pandas, Numpy, NLTK, Matplotlib, Seaborn, WordCloud, Streamlit, and more.
• NLP Expertise: Gained proficiency in NLP concepts like Tokenization, stopword removal, stemming, term frequency-inverse document frequency, etc.

How to Use

1. Clone Repository:

   git clone https://github.com/your-username/spam-classifier.git
   cd spam-classifier
   

2. Install Dependencies:

   pip install -r requirements.txt
   

3. Run the Streamlit App:

   streamlit run app.py
   

4. Access the App: Open your browser and go to http://localhost:8501.

5. Input: Provide the text you want to classify.

6. Output: The app will predict whether the input is spam or legitimate.

This project demonstrates excellence in spam detection, leveraging Streamlit for an interactive and seamless user experience. #MachineLearning #NLP #SpamClassification #Streamlit 🤖📤📥