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This repository allows Curated News users to see how our open source news headlines text classifier works and operates. It will also allow researchers and academics to vet and verify the strength of our modeling approaches.
This project uses the language model API to identify and extract names, dates, and locations from text, functioning similarly to a named entity recognition (NER).
This project is a web-based spam detector built with Flask and a Multinomial Naive Bayes classifier from scikit-learn. It classifies messages as "Spam" or "Not Spam" based on a trained dataset. The application features a user-friendly interface that works seamlessly on both mobile and web platforms for real-time spam prediction.
Tools for automatic frame discovery and labeling based on topic modeling and deep learning, made widely accessible to researchers from non computational backgrounds.