⭐ FLAGSHIP PROJECT
Insurance Premium Predictor
End-to-end machine learning web application that predicts insurance premiums in real-time. Features a production-grade FastAPI backend with Pydantic validation, Dockerized and deployed on AWS, dual frontend interfaces via Flask and Streamlit, with a live Vercel-hosted demo.
FastAPIFlask
StreamlitDocker
AWSScikit-learn
PythonVercel
→ View Live Demo
→ Frontend Repo
→ Backend Repo
⭐ FLAGSHIP PROJECT
DocuMind Q&A (RAG Pipeline)
Production-ready Retrieval-Augmented Generation system that ingests PDFs, creates
semantic vector embeddings with Chroma, and answers complex questions using LangChain + Gemini . Features
multi-document support, conversation memory, streaming responses, and source citations.
LangChainGemini
RAGChroma
StreamlitPython
→ View on GitHub
⭐ FEATURED
Food Vision 101 Improved
Reproduced and improved a published research paper on Food classification with 101
classes
CNNTransfer Learning
TensorFlowPython
Fine-TuningNeural Networks
→ View on GitHub
⭐ FEATURED
SkimLit
Recreated and fine-tuned a research-grade NLP pipeline for sequential sentence
classification in medical abstracts.
NLPDeep Learning
PythonTensorFlow
→ View on GitHub
DDOS Attack Detection using Machine Learning
Built a machine learning based DDoS attack detection system that analyzes network traffic
patterns to identify anomalies in near real time to classify malicious traffic with high accuracy.
Machine LearningPython
Scikit-learnPandas
SeabornNumpy
Matplotlib
→ View on GitHub
Near-Earth Asteroid Tracker
A modern space-themed web app that tracks and displays near-Earth asteroids approaching
our planet within a 7-day window using NASA`s NeoWs (Near Earth Object Web Service) API.
JavaScriptHTML
APICSS
→
View on GitHub
Diamond Price Prediction
This is a diamond price prediction tool developed using machine learning algorithms such
as Linear Regression, Support Vector Regression (SVR), and Decision Tree Regression. Built as a Python-based
application, it takes input features like carat weight, cut, color, clarity, and other relevant attributes
to estimate the price of a diamond. The models were trained on real-world datasets to ensure high prediction
accuracy.
PythonMachine Learning
Support Vector MachineLinear Regression
→
View on GitHub