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MLOps Project Documentation

Welcome to the documentation for the MLOps Fake News Detection project by Group 102.

Project Overview

This project implements a deep neural network for fake news detection using PyTorch. The focus is on understanding the end-to-end machine learning lifecycle rather than model complexity.

Dataset: 44,919 news articles with title, text, and binary classification (fake/real) Model: LSTM-based Recurrent Neural Network Framework: PyTorch with comprehensive MLOps tooling

  • Workflow - Development workflow and project structure
  • Running Locally - Setup and run the project on your machine

Team

  • Julius Gregers Gliese Winkel (s234862)
  • Rune Daugaard Harlyk (s234814)
  • Christian Amtoft Nickelsen (s234863)
  • Joseph An Duy Nguyen (s234826)