A full-stack exploration of accident risk prediction and interactive geospatial modeling. When the Kaggle Playground Series S5E10 launched a challenge to predict road accident risk,...
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Applications on Tarterware
Deployed on AWS

Road Risk Playground
A full-stack web application that estimates the relative accident risk for any driving route. Built with React, TypeScript, and Mapbox GL on the front end, it connects to a Python backend running in AWS Lambda. The app analyzes route geometry, lighting, and weather conditions using a trained machine-learning model, all deployed through Terraform to an S3 and CloudFront infrastructure. Click photo above or go to https://road-risk-playground.tarterware.com/

Playing Card Classifier
An interactive web app that identifies a playing card from an uploaded or camera image. The model, built with TensorFlow, runs on AWS Lambda through a lightweight Python backend, while the React + TypeScript front end is hosted on Amazon S3 and served via CloudFront. It demonstrates serverless machine-learning inference and real-time user interaction in the browser. Click photo above or go to https://card-classifier.tarterware.com/
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Blog Posts
Calculating Road Curviness: A Practical Approach with Mapbox and Python
This month’s Kaggle Playground Prediction competition is Predicting Road Accident Risk. This competition includes a second part to create a web application that uses the...
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