AI Fake News Detection System
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About this role
Python, Data Processing, Web Scraping, Software Architecture, Machine Learning (ML), Data Science, Data Analysis, REST API · I’m creating a production-ready AI/ML solution that automatically reviews articles pulled from news websites and flags any item that is likely to be fake. All content will be in English, and the system must consistently reach at least 90 % accuracy on an independent validation set; precision and recall should be reported alongside overall accuracy so I can see how it performs on both real and fabricated pieces.
The workflow I have in mind combines three parts: • an automated pipeline that scrapes or ingests fresh articles, cleans the text, and stores it in a structured format; • a robust NLP model—think transformer-based architecture fine-tuned on a well-curated fake-vs-real news dataset—trained and evaluated in Python with libraries such as PyTorch, TensorFlow or Scikit-learn; • a lightweight interface (REST API or simple web demo) that returns the probability of falseness plus the key features that influenced the decision for transparency.
Deliverables • End-to-end codebase with clear instructions (requirements.txt / environment.yml, README) • Trained model weights and scripts to reproduce training and evaluation • Detailed report showing dataset splits, confusion m