A Python/Flask API that serves three Hugging Face AI models: Sentiment Analysis, Zero-Shot Classification, and Named Entity Recognition (NER). Option 2 (Longer & More Descriptive) A multi-task AI microservice built with Python and Flask. Serves pre-traine

This project aims to develop a system that can automatically detect biased and unbiased news articles. Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

A Gradio-powered web app integrating multiple Hugging Face models for tasks like chat, image generation, captioning, object detection, text summarization, and named entity recognition. Built with Python, Transformers, and Stable Diffusion.

NLP Techniques on comedy corpora

NEL by MS is a clean and minimalist web application designed to deliver streamlined functionality with an elegant user interface. The app focuses on simplicity and usability, providing users with an efficient and pleasant digital experience through a well-structured layout and intuitive design elements. Built with modern web technologies!

A Streamlit app that performs Named Entity Recognition (NER), links entities to Wikipedia, and handles disambiguation for ambiguous terms like "Apple," using NLP techniques.

This API uses spaCy's pre-trained models for Named Entity Recognition (NER) and Sentiment Analysis. NER is powered by the spaCy en_core_web_trf transformer model, while sentiment analysis uses a custom-trained transformer model. Built with Flask, the API offers simple endpoints for processing JSON requests and responses.