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Classification of Emails Using Artificial Intelligence

IHK Dortmund - Abschluss Projekt

Titel: Klassifizierung von E-Mails mithilfe Künstler Intelligenz Author: Philipp Braun Conclusion: Fachinformatiker für Anwendungsentwicklung

Company: Sylvenstein Media GmbH

Training-operation: QualifzierungsAkademie Rheinruhr GmbH & CO.KG.

This repository contains the implementation of a machine learning model for classifying emails based on their content. The project was developed as part of my final year project in computer science, and aims to showcase my skills in Artificial Intelligence, Machine Learning, and Natural Language Processing.

Overview

The primary goal of this project is to create an efficient and accurate email classification system that can automatically categorize incoming emails into different folders or tags, based on their content. This system can help users manage their email inboxes more effectively and save time by filtering out irrelevant or spam messages.

The project is implemented in Python, and it leverages various machine learning and natural language processing techniques, such as:

  • Text preprocessing (tokenization, stopword removal, and stemming)
  • Feature extraction (TF-IDF)
  • Model training and evaluation (using algorithms such as Naive Bayes, Support Vector Machines, and Random Forest)

Most of the work for this project was done using Jupyter Notebooks. The repository contains several notebooks that were used for researching and learning Data Science concepts. In the 'Source Code' folder, you can find the main notebooks of the project, which provide a detailed explanation of the AI-related components. Due to data security concerns, the complete implementation of the solution cannot be shared; however, the main notebooks provide valuable insights into the core concepts and techniques used in the project.

Getting Started

Prerequisites

To run the project, you need to have Python 3.x installed along with the following libraries:

  • numpy
  • pandas
  • scikit-learn
  • nltk
  • jupyter

Installation

  1. Clone the repository: git clone https://github.com/braun-devwtf/Classification-of-emails-using-artificial-intelligence.git

  2. Install the required libraries:

    pip install -r requirements.txt

Usage

After setting up the project, you can start exploring the email classification system by running Jupyter Notebook:

jupyter notebook

Navigate to the 'Source Code' folder and open the main notebooks to learn more about the AI-related components of the project.

Documentation

For a detailed description of the project, please refer to the project documentation (in German).

Author

[Philipp Braun] - Final Year Project - braun-devwtf

License

This project is licensed under the MIT License - see the LICENSE file for details.the LICENSE file for details.

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