AI Email Classifier

An AI Application for classifying emails into categories

Features

• Leverages both Machine Learning (ML) and Deep Learning (DL) models:
  • Offers flexibility and the ability to choose the most suitable model for different datasets and classification tasks.
• High Accuracy: Demonstrates high accuracy on unseen datasets, ensuring reliable and effective email categorization.
• User-Friendly Web Interface: Provides a clean and intuitive interface for:
  • Training: Easily train and fine-tune the models using labeled email datasets. ( Testing: Conveniently test the classifier with individual emails or batches of emails.
• REST API Gateway: Enables seamless integration with other applications:
  • Single Email Classification: Classifies a single email by sending its subject and body in a request.
  • Batch Email Classification: Efficiently classifies a large number of emails in a single API call.

Prerequisites: 📖

• Git: If you haven't already, install Git from https://git-scm.com/downloads.
• Python 3.x: Download and install Python 3 from https://www.python.org/downloads/.

Installation: 🚀

1. Open a terminal or command prompt and navigate to your desired project directory. Then,

   • Run the following command to clone the Ai Email Classifier repository from GitHub:

     git clone https://github.com/TheThinker01/AiEmailClassifier.git

   • Install Python virtualenv

     pip install virtualenv

2. Create and Activate a Virtual Environment (Recommended): bash virtualenv env # Create a virtual environment named 'env' source env/bin/activate # Activate the virtual environment (Linux/macOS)

   • For Windows, activate the virtual environment using:

     env\Scripts\activate.bat # Activate the virtual environment (Windows)

3. Install all the dependencies -

   pip install -r Requirements.txt

4. Run the Server -

   python manage.py runserver 127.0.0.1:8000

5. Access the Application:

   • Open the specified URL (e.g., http://127.0.0.1:8000/ml) in your web browser. 🎉

Requirements

• All required packages and libraries are listed in the Requirements.txt file.

Credits - Collaborative Effort by Team - AI200416

• Thanks to the following contributors: Archisman Pathak