/IT-Ticket-Predict

Primary LanguageJupyter Notebook

IT-Ticket-Predict

This project aims to categorize IT tickets using machine learning models. It utilizes the dataset (tickets.csv) to train and evaluate different models including Naive Bayes, Logistic Regression, and SVM. Confusion matrices are saved in the Resources folder.

Tech Stack

  • Flask: Backend server
  • HTML/CSS: Frontend
  • Python: Programming language
  • Scikit-Learn: Machine learning library
  • Jupyter Notebook: Interactive development

Installation Instructions

  1. Clone the Repository:

    git clone https://github.com/your-username/IT-Ticket-Predict.git

  2. Navigate to the Project Directory:

    cd IT-Ticket-Predict

  3. Set up a Virtual Environment (recommended):

    python3 -m venv venv
source venv/bin/activate  # On Windows, use: venv\Scripts\activate

  4. Install Required Packages:

    pip install -r requirements.txt

  5. Run the Flask Application:

    flask run

  6. Access the Application: Open your browser and go to:

    http://127.0.0.1:5000/

How to Run Jupyter Notebooks

  1. Activate the virtual environment:

    source venv/bin/activate

  2. Start the Jupyter notebook server:

    jupyter notebook

  3. Open source.ipynb to interact with the project.