📧 Spam Email Classifier using Naïve Bayes and NLP

This project is a Spam Email Classifier that detects spam vs. non-spam (ham) messages using Natural Language Processing (NLP) and Machine Learning (ML).

🚀 Features

• Uses Naïve Bayes Classifier for text classification
• Preprocesses text (removes stopwords, punctuation, and converts to lowercase)
• Uses TF-IDF Vectorization for feature extraction
• Achieves high accuracy (~97–99%) on the dataset

📂 Dataset

• The dataset used is spam.csv, which contains labeled spam and ham messages.
• Columns:
  • Category: Spam or Ham
  • Message: The actual text message

🛠️ Installation & Usage

1. Clone the repo:

   git clone https://github.com/najeeb-08/Spam-Email-Classifier.git
   cd Spam-Email-Classifier

2. Install dependencies:

   pip install pandas numpy sklearn nltk

3. Run the script:

   python spam_classifier.py

📊 Model Performance

• Accuracy: ~97–99%
• Precision/Recall/F1-Score: High scores indicating good spam detection

📜 License

This project is open-source under the MIT License.

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🔹 Contributions are welcome! Feel free to fork and improve the model.
📩 Contact: najeeb-08