Fine-tuned roberta-base classifier on the LIAR dataset. Aaccepts multiple input types text, URLs, and PDFs and outputs a prediction with a confidence score. It also leverages google/flan-t5-base to generate explanations and uses an Agentic AI with LangGraph to orchestrate agents for planning, retrieval, execution, fallback, and reasoning.

Predicts maternal health risk levels (low/mid/high) using a Random Forest model and a Flask web interface.

AI-Powered Eye Disease Detection Web App An intelligent retina image classification system built using deep learning (VGG16), TensorFlow, and Flask. This open-source project helps detect common eye diseases like Cataract, Diabetic Retinopathy, and Glaucoma, and also identifies uncertain cases as Unknown.

Welcome to the example code repository for the "BentoML Practical Guide"! This repository contains all the example code and practical use cases from the book, designed to help you better understand and apply BentoML for model service and deployment.