I developed a convolutional neural network regression in Python using Keras with a TensorFlow back-end to drive a car virtually around a track. I improved on the well-known NVIDIA neural network for end-to-end deep learning for self-driving cars and achieved a 100 % success rate on the most difficult track.

This portfolio project demonstrates a Flask based implementation of a secure user model with registration, email confirmation, and Google OAuth 2 login, combined with an example of a catalog of items that's grouped in categories.

Registered users can CRUD the catalog via a web front-end or via a REST API that adheres strictly to the JSON API 1.0 specification. The REST API supports advanced searching and filtering. End-to-end scenarios are demonstrated via a Python client written in a Jupyter notebook.

This is a project that involves a Knockout and Bootstrap based single page application. It features a neighborhood map with interesting locations.

The application was developed using the Knockout library to easily associate HTML DOM elements with the model data in the JavaScript functions and to automatically update the UI when the model data changes.

The application demonstrates the integration of third-party APIs from Google Maps and Foursquare.

For all devices, attractive styling and intuitive responsive behavior was implemented with Bootstrap 4.