Deep Learning-Based Fake News Detection

This project focuses on the development of a Python-based API designed to detect misleading articles (fake news) and identify content generated by artificial intelligence. The system leverages advanced Natural Language Processing (NLP) and deep learning models to analyze and classify textual data.

The detection mechanism uses models such as BERT and GPT to evaluate the authenticity of articles and determine whether the content is human-written or AI-generated. In addition, article compression and summarization techniques are applied using T5 to optimize processing efficiency and reduce the amount of data analyzed.

The API is designed to be easily integrated into other applications or platforms, enabling automated verification of online content and helping combat the spread of misinformation.