fake-news and NLP_FakeNewsDetection
These are **competitors** — both implement independent end-to-end fake news detection pipelines using standard ML/deep learning approaches on news datasets, with no shared dependencies or complementary functionality that would require using them together.
About fake-news
mihail911/fake-news
Building a fake news detector from initial ideation to model deployment
Implements dual classification approaches—a Scikit-learn random forest baseline and a RoBERTa transformer model via PyTorch Lightning—with experiment tracking through MLflow and data versioning via DVC. The pipeline includes SHAP-based model interpretability, Great Expectations data validation, and PyTest-driven testing, deployed as a FastAPI/Gunicorn REST service containerized with Docker and integrated into a Chrome extension for end-user interaction.
About NLP_FakeNewsDetection
tychen5/NLP_FakeNewsDetection
Using machine learning & deep learning to analyze the News
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