Imagination Trumps Knowledge!
Featured ProjectReimagining Walmart's Shoping Experience
Built an intelligent AI shopping agent using LangGraph that turns natural language recipes into personalized grocery lists. Integrated with a Walmart-clone platform, the agent fetches relevant ingredients, suggests brands, and adds user-preferred items to the cart. Powered by Supabase, FastAPI, WebSockets, and a modern Next.js + React frontend.
LangGraph • FastAPI • WebSockets • Next.js • React • Supabase
Open Source | PyPI PackageVisualize PyTorch and Keras neural networks as 2D diagrams and interactive 3D models. Built to help beginners understand deep learning architectures.ModelViz-AI
Python • PyTorch • Keras • TensorFlow • PyPI • GraphViz
Open Source | PyPI PackageBuilt using Python and FastMCP, enabling programmatic creation, deletion, and retrieval of reminders directly from macOS. Integrated AppleScript automation with a standardized MCP interface to support seamless interaction with Claude Code and other AI-powered developer tools.Apple Reminders MCP Server (MacOS Application)
Python • FastMCP • AppleScript • macOS • PyPI • Claude Code
ProjectA context-aware Retrieval-Augmented Generation (RAG) system designed to enhance response accuracy by intelligently retrieving only the most relevant information based on the context of user queries. The system incorporated metadata tagging to effectively categorize and organize documents, enabling efficient retrieval of specific content chunks. This approach significantly improved performance by reducing noise and ensuring that the generation model received high-quality, contextually appropriate data for response generation.Contextual Retrieval RAG Bot
RAG • LangChain • Vector Database • NLP • Python • Huggingface Embeddings
ProjectDeveloped a KNN-based Food Recommendation System trained on a public dataset comprising 48,735 entries and 12 user dietary features, using TfidfVectorizer for effective feature extraction to deliver personalized food suggestions based on individual preferences. To enhance the recommendation quality and variety, I integrated the Spoonacular API, providing access to over 600,000 products, 5,000+ recipes, and 115,000+ menu items, enriched with detailed data on nutrition, pricing, and cooking tips. The system was built with a Flask backend and an HTML/CSS frontend, enabling users to receive real-time, customized food recommendations.Food Recommendation System
Python • KNN • Flask • Spoonacular API • TfidfVectorizer • HTML/CSS
ProjectDuring a hackathon, I developed a Diabetes Prediction Model using Artificial Neural Networks (ANN), achieving 85% accuracy on a public dataset containing 1,000 records and 13 key health indicators such as insulin levels, glucose, and blood pressure. To make the model accessible and user-friendly, I built a full-stack web application featuring a React + JSX frontend and a Flask backend. This application allows users to input real-time health data and receive instant diabetes risk predictions, supporting early assessment and proactive health management.Early Stage Diabetes Prediction
Python • ANN • React • Flask • Machine Learning • Healthcare AI